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Kashima, Hisashi

Graduate School of Informatics, Department of Informatics Professor

Kashima, Hisashi
list
    Last Updated :2023/09/27

    Basic Information

    Faculty

    • 工学部

    Concurrent Affiliation

    • Center for the Promotion of Interdisciplinary Education and Research (C-PiER), 超高齢社会デザイン価値創造ユニット
    • Center for the Promotion of Interdisciplinary Education and Research (C-PiER), 人工知能研究ユニット

    Academic Degree

    • 修士（工学）(京都大学)
    • 博士（情報学）(京都大学)

    Research History

    • From Apr. 2014, To Present
      Kyoto University, Graduate School of Informatics, Professor
    • From Oct. 2016, To Mar. 2020
      RIKEN Center for AIP, Human Computation Team, Team Leader
    • From Aug. 2009, To Mar. 2013
      The University of Tokyo, Graduate School of Information Science and Technology, Associate Professor
    • From Apr. 1999, To Jul. 2009
      IBM Research, Tokyo Research Laboratory, Researcher

    ID,URL

    researchmap URL

    list
      Last Updated :2023/09/27

      Research

      Research Interests

      • Data Analytics
      • Artificial Intelligence
      • Crowdsourcing
      • Human Computation
      • Machine learning
      • Data mining

      Research Areas

      • Informatics, Intelligent informatics

      Papers

      • Making individually fair predictions with causal pathways.
        Yoichi Chikahara; Shinsaku Sakaue; Akinori Fujino; Hisashi Kashima
        Data Mining and Knowledge Discovery, 2023
      • Feature selection for discovering distributional treatment effect modifiers.
        Yoichi Chikahara; Makoto Yamada; Hisashi Kashima
        Uncertainty in Artificial Intelligence(UAI), 2022
      • Predicting Anesthetic Infusion Events Using Machine Learning
        Naoki Miyaguchi; Koh Takeuchi; Hisashi Kashima; Mizuki Morita; Hiroshi Morimatsu
        Scientific Reports, 19 Nov. 2021, Peer-reviewed
      • マイクロタスク型クラウドソーシングによるリバーシの試み
        佐々木, 優; 平木, 理恵; 馬場, 雪乃; 森嶋, 厚行; 鹿島, 久嗣
        Proc. of JSAI, 2016
      • 遺伝子構造キュレーションのクラウドソーシング・タスク設計
        神沼 英里; 馬場 雪乃; 藤澤 貴智; 鹿島 久嗣; 中村 保一
        人工知能学会全国大会論文集, 2014
      • Multiview Representation Learning from Crowdsourced Triplet Comparisons.
        Xiaotian Lu; Jiyi Li; Koh Takeuchi; Hisashi Kashima
        WWW, 2023
      • Mitigating Observation Biases in Crowdsourced Label Aggregation.
        Ryosuke Ueda; Koh Takeuchi; Hisashi Kashima
        ICPR, 2022
      • Interpretable Knowledge Tracing: Simple and Efficient Student Modeling with Causal Relations.
        Sein Minn; Jill-Jênn Vie; Koh Takeuchi; Hisashi Kashima; Feida Zhu 0001
        AAAI, 2022
      • Bayesian optimization with partially specified queries.
        Shogo Hayashi; Junya Honda; Hisashi Kashima
        Machine Learning, 2022
      • Link Prediction in Chemical Compound Network Under Observation Bias
        INUI Takumi; HARADA Shonosuke; YANG Liu; TAKEUCHI Kou; TAKIGAWA Ichigaku; YAMANISHI Yoshihiro; KASHIMA Hisashi
        Proceedings of the Annual Conference of JSAI, 2022
      • Improving imbalanced classification using near-miss instances.
        Akira Tanimoto; So Yamada; Takashi Takenouchi; Masashi Sugiyama; Hisashi Kashima
        Expert Syst. Appl., 2022
      • Context-aware spatio-temporal event prediction via convolutional Hawkes processes
        Maya Okawa; Tomoharu Iwata; Yusuke Tanaka; Takeshi Kurashima; Hiroyuki Toda; Hisashi Kashima
        Machine Learning, Aug. 2022
      • CrowdR&D: クラウド協働評価のための参加型R&Dプロジェクト情報統合基盤
        神沼 英里; 望月 芳樹; 藤澤 貴智; 馬場 雪乃; 藤山 秋佐夫; 鹿島 久嗣; 中村 保一
        人工知能学会全国大会論文集, 2016
      • Crowdsourcing Evaluation of Saliency-Based XAI Methods.
        Xiaotian Lu; Arseny Tolmachev; Tatsuya Yamamoto; Koh Takeuchi; Seiji Okajima; Tomoyoshi Takebayashi; Koji Maruhashi; Hisashi Kashima
        Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track - European Conference, 2021
      • Inter-domain Multi-relational Link Prediction.
        Luu Huu Phuc; Koh Takeuchi; Seiji Okajima; Arseny Tolmachev; Tomoyoshi Takebayashi; Koji Maruhashi; Hisashi Kashima
        Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, 2021
      • In-Vehicle Network Attack Detection Across Vehicle Models: A Supervised-Unsupervised Hybrid Approach.
        Shu Nakamura; Koh Takeuchi; Hisashi Kashima; Takeshi Kishikawa; Takashi Ushio; Tomoyuki Haga; Takamitsu Sasaki
        24th IEEE International Intelligent Transportation Systems Conference(ITSC), 2021
      • Deep Mixture Point Processes
        Maya Okawa; Tomoharu Iwata; Takeshi Kurashima; Yusuke Tanaka; Hiroyuki Toda; Naonori Ueda; Hisashi Kashima
        Transactions of the Japanese Society for Artificial Intelligence, 01 Sep. 2021
      • Dynamic Hawkes Processes for Discovering Time-evolving Communities' States behind Diffusion Processes.
        Maya Okawa; Tomoharu Iwata; Yusuke Tanaka 0002; Hiroyuki Toda; Takeshi Kurashima; Hisashi Kashima
        KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining(KDD), 2021
      • Crowdsourcing Evaluation of Saliency-based XAI Methods.
        Xiaotian Lu; Arseny Tolmachev; Tatsuya Yamamoto; Koh Takeuchi; Seiji Okajima; Tomoyoshi Takebayashi; Koji Maruhashi; Hisashi Kashima
        CoRR, 2021
      • Inter-domain Multi-relational Link Prediction.
        Luu Huu Phuc; Koh Takeuchi; Seiji Okajima; Arseny Tolmachev; Tomoyoshi Takebayashi; Koji Maruhashi; Hisashi Kashima
        CoRR, 2021
      • Re-evaluating Word Mover's Distance.
        Ryoma Sato; Makoto Yamada; Hisashi Kashima
        CoRR, 2021
      • Dynamic Hawkes Processes for Discovering Time-evolving Communities' States behind Diffusion Processes.
        Maya Okawa; Tomoharu Iwata; Yusuke Tanaka 0002; Hiroyuki Toda; Takeshi Kurashima; Hisashi Kashima
        CoRR, 2021
      • Computationally Efficient Wasserstein Loss for Structured Labels.
        Ayato Toyokuni; Sho Yokoi; Hisashi Kashima; Makoto Yamada
        CoRR, 2021
      • Causal Combinatorial Factorization Machines for Set-Wise Recommendation.
        Akira Tanimoto; Tomoya Sakai 0001; Takashi Takenouchi; Hisashi Kashima
        Advances in Knowledge Discovery and Data Mining - 25th Pacific-Asia Conference, 2021
      • Computationally Efficient Wasserstein Loss for Structured Labels.
        Ayato Toyokuni; Sho Yokoi; Hisashi Kashima; Makoto Yamada
        Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Student Research Workshop, 2021
      • Grab the Reins of Crowds: Estimating the Effects of Crowd Movement Guidance Using Causal Inference.
        Koh Takeuchi; Ryo Nishida; Hisashi Kashima; Masaki Onishi
        AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems(AAMAS), 2021
      • Regret Minimization for Causal Inference on Large Treatment Space.
        Akira Tanimoto; Tomoya Sakai 0001; Takashi Takenouchi; Hisashi Kashima
        The 24th International Conference on Artificial Intelligence and Statistics(AISTATS), 2021
      • Learning Individually Fair Classifier with Path-Specific Causal-Effect Constraint.
        Yoichi Chikahara; Shinsaku Sakaue; Akinori Fujino; Hisashi Kashima
        The 24th International Conference on Artificial Intelligence and Statistics(AISTATS), 2021
      • Learning to Rank for Multi-Step Ahead Time-Series Forecasting.
        Jiuding Duan; Hisashi Kashima
        IEEE Access, 2021
      • Dual graph convolutional neural network for predicting chemical networks.
        Shonosuke Harada; Hirotaka Akita; Masashi Tsubaki; Yukino Baba; Ichigaku Takigawa; Yoshihiro Yamanishi; Hisashi Kashima
        BMC bioinformatics, 23 Apr. 2020
      • DDBJ Data Analysis Challenge: a machine learning competition to predict Arabidopsis chromatin feature annotations from DNA sequences.
        Eli Kaminuma; Yukino Baba; Masahiro Mochizuki; Hirotaka Matsumoto; Haruka Ozaki; Toshitsugu Okayama; Takuya Kato; Shinya Oki; Takatomo Fujisawa; Yasukazu Nakamura; Masanori Arita; Osamu Ogasawara; Hisashi Kashima; Toshihisa Takagi
        Genes & genetic systems, 22 Apr. 2020, Peer-reviewed
      • Poincare: Recommending Publication Venues via Treatment Effect Estimation.
        Ryoma Sato; Makoto Yamada; Hisashi Kashima
        CoRR, 2020
      • GraphITE: Estimating Individual Effects of Graph-structured Treatments.
        Shonosuke Harada; Hisashi Kashima
        CoRR, 2020
      • Chemical Property Prediction Under Experimental Biases.
        Yang Liu; Hisashi Kashima
        CoRR, 2020
      • CrowDEA: Multi-view Idea Prioritization with Crowds.
        Yukino Baba; Jiyi Li; Hisashi Kashima
        CoRR, 2020
      • Regret Minimization for Causal Inference on Large Treatment Space.
        Akira Tanimoto; Tomoya Sakai 0001; Takashi Takenouchi; Hisashi Kashima
        CoRR, 2020
      • Fast Unbalanced Optimal Transport on Tree.
        Ryoma Sato; Makoto Yamada; Hisashi Kashima
        CoRR, 2020
      • Counterfactual Propagation for Semi-Supervised Individual Treatment Effect Estimation.
        Shonosuke Harada; Hisashi Kashima
        CoRR, 2020
      • Random Features Strengthen Graph Neural Networks.
        Ryoma Sato; Makoto Yamada; Hisashi Kashima
        CoRR, 2020
      • Fast and Robust Comparison of Probability Measures in Heterogeneous Spaces.
        Ryoma Sato; Marco Cuturi; Makoto Yamada; Hisashi Kashima
        CoRR, 2020
      • Counterfactual Propagation for Semi-supervised Individual Treatment Effect Estimation.
        Shonosuke Harada; Hisashi Kashima
        Machine Learning and Knowledge Discovery in Databases - European Conference, 2020
      • Fast Unbalanced Optimal Transport on a Tree.
        Ryoma Sato; Makoto Yamada; Hisashi Kashima
        Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020(NeurIPS), 2020
      • Performance as a Constraint: An Improved Wisdom of Crowds Using Performance Regularization.
        Jiyi Li; Yasushi Kawase; Yukino Baba; Hisashi Kashima
        Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence(IJCAI), 2020
      • An Intransitivity Model for Matchup and Pairwise Comparison.
        Yan Gu; Jiuding Duan; Hisashi Kashima
        25th International Conference on Pattern Recognition(ICPR), 2020
      • Fast Deterministic CUR Matrix Decomposition with Accuracy Assurance.
        Yasutoshi Ida; Sekitoshi Kanai; Yasuhiro Fujiwara; Tomoharu Iwata; Koh Takeuchi; Hisashi Kashima
        Proceedings of the 37th International Conference on Machine Learning(ICML), 2020
      • Topological Bayesian Optimization with Persistence Diagrams.
        Tatsuya Shiraishi; Tam Le; Hisashi Kashima; Makoto Yamada
        ECAI 2020 - 24th European Conference on Artificial Intelligence(ECAI), 2020
      • Stress Prediction from Head Motion.
        Hitoshi Kusano; Yuji Horiguchi; Yukino Baba; Hisashi Kashima
        7th IEEE International Conference on Data Science and Advanced Analytics(DSAA), 2020
      • Simultaneous Link Prediction on Unaligned Networks Using Graph Embedding and Optimal Transport.
        Luu Huu Phuc; Koh Takeuchi; Makoto Yamada; Hisashi Kashima
        7th IEEE International Conference on Data Science and Advanced Analytics(DSAA), 2020
      • Synthetic accessibility assessment using auxiliary responses.
        Shun Ito; Yukino Baba; Tetsu Isomura; Hisashi Kashima
        Expert Syst. Appl., 2020
      • 超問題：専門知識を要するクラウドソーシングタスクの回答統合法
        李, 吉屹; 馬場, 雪乃; 鹿島, 久嗣
        日本データベース学会和文論文誌, Mar. 2019, Peer-reviewed
      • Approximation Ratios of Graph Neural Networks for Combinatorial Problems.
        Ryoma Sato; Makoto Yamada; Hisashi Kashima
        CoRR, 2019
      • Topological Bayesian Optimization with Persistence Diagrams.
        Tatsuya Shiraishi; Tam Le; Hisashi Kashima; Makoto Yamada
        CoRR, 2019
      • Learning to Find Hard Instances of Graph Problems.
        Ryoma Sato; Makoto Yamada; Hisashi Kashima
        CoRR, 2019
      • Theoretical evidence for adversarial robustness through randomization: the case of the Exponential family.
        Rafael Pinot; Laurent Meunier; Alexandre Araujo; Hisashi Kashima; Florian Yger; Cédric Gouy-Pailler; Jamal Atif
        CoRR, 2019
      • Constant Time Graph Neural Networks.
        Ryoma Sato; Makoto Yamada; Hisashi Kashima
        CoRR, 2019
      • Large-scale Driver Identification Using Automobile Driving Data.
        Daiki Tanaka; Yukino Baba; Hisashi Kashima; Yuta Okubo
        2019 IEEE International Conference on Systems, Man and Cybernetics(SMC), 2019
      • Theoretical evidence for adversarial robustness through randomization.
        Rafael Pinot; Laurent Meunier; Alexandre Araujo; Hisashi Kashima; Florian Yger; Cédric Gouy-Pailler; Jamal Atif
        Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019(NeurIPS), 2019
      • Fast Sparse Group Lasso.
        Yasutoshi Ida; Yasuhiro Fujiwara; Hisashi Kashima
        Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019(NeurIPS), 2019
      • In-Vehicle Network Intrusion Detection and Explanation Using Density Ratio Estimation.
        Daiki Tanaka; Makoto Yamada; Hisashi Kashima; Takeshi Kishikawa; Tomoyuki Haga; Takamitsu Sasaki
        2019 IEEE Intelligent Transportation Systems Conference(ITSC), 2019
      • Long-Term Prediction of Small Time-Series Data Using Generalized Distillation.
        Shogo Hayashi; Akira Tanimoto; Hisashi Kashima
        International Joint Conference on Neural Networks(IJCNN), 2019
      • Interdependence Model for Multi-label Classification.
        Kosuke Yoshimura; Tomoaki Iwase; Yukino Baba; Hisashi Kashima
        Artificial Neural Networks and Machine Learning - ICANN 2019: Text and Time Series - 28th International Conference on Artificial Neural Networks, 2019
      • Probabilistic Modeling of Peer Correction and Peer Assessment.
        Takeru Sunahase; Yukino Baba; Hisashi Kashima
        Proceedings of the 12th International Conference on Educational Data Mining(EDM), 2019
      • Active Change-Point Detection.
        Shogo Hayashi; Yoshinobu Kawahara; Hisashi Kashima
        Proceedings of The 11th Asian Conference on Machine Learning(ACML), 2019
      • Learning to Sample Hard Instances for Graph Algorithms.
        Ryoma Sato; Makoto Yamada; Hisashi Kashima
        Proceedings of The 11th Asian Conference on Machine Learning(ACML), 2019
      • Knowledge Tracing Machines: Factorization Machines for Knowledge Tracing.
        Jill-Jênn Vie; Hisashi Kashima
        The Thirty-Third AAAI Conference on Artificial Intelligence(AAAI), 2019
      • Approximation Ratios of Graph Neural Networks for Combinatorial Problems.
        Ryoma Sato; Makoto Yamada; Hisashi Kashima
        Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019(NeurIPS), 2019, Peer-reviewed
      • Context-Regularized Neural Collaborative Filtering for Game App Recommendation.
        Shonosuke Harada; Kazuki Taniguchi; Makoto Yamada; Hisashi Kashima
        Proceedings of ACM RecSys 2019 Late-Breaking Results co-located with the 13th ACM Conference on Recommender Systems, RecSys 2019 Late-Breaking Results, Copenhagen, Denmark, September 16-20, 2019., 2019, Peer-reviewed
      • Crownn: Human-in-the-loop Network with Crowd-generated Inputs.
        Yusuke Sakata; Yukino Baba; Hisashi Kashima
        Proceedings of the 44th International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2019, Peer-reviewed
      • 教育用データ解析コンペティション基盤の設計と実践
        馬場, 雪乃; 高瀬, 朝海; 新, 恭兵; 小山, 聡; 鹿島, 久嗣
        情報処理学会デジタルプラクティス, Oct. 2018
      • Wisdom of crowds for synthetic accessibility evaluation
        Yukino Baba; Tetsu Isomura; Hisashi Kashima
        Journal of Molecular Graphics and Modelling, 01 Mar. 2018, Peer-reviewed
      • Matrix- and tensor-based recommender systems for the discovery of currently unknown inorganic compounds
        Seko Atsuto; Hayashi Hiroyuki; Kashima Hisashi; Tanaka Isao
        PHYSICAL REVIEW MATERIALS, 16 Jan. 2018, Peer-reviewed
      • Knowledge Tracing Machines: Factorization Machines for Knowledge Tracing.
        Jill-Jênn Vie; Hisashi Kashima
        CoRR, 2018
      • BayesGrad: Explaining Predictions of Graph Convolutional Networks.
        Hirotaka Akita; Kosuke Nakago; Tomoki Komatsu; Yohei Sugawara; Shin-ichi Maeda; Yukino Baba; Hisashi Kashima
        CoRR, 2018
      • Incorporating Worker Similarity for Label Aggregation in Crowdsourcing.
        Jiyi Li; Yukino Baba; Hisashi Kashima
        Artificial Neural Networks and Machine Learning - ICANN 2018 - 27th International Conference on Artificial Neural Networks, 2018
      • Short-Term Precipitation Prediction with Skip-Connected PredNet.
        Ryoma Sato; Hisashi Kashima; Takehiro Yamamoto
        Artificial Neural Networks and Machine Learning - ICANN 2018 - 27th International Conference on Artificial Neural Networks, 2018
      • Simultaneous Clustering and Ranking from Pairwise Comparisons.
        Jiyi Li; Yukino Baba; Hisashi Kashima
        Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, IJCAI 2018, July 13-19, 2018, Stockholm, Sweden., 2018, Peer-reviewed
      • 結晶化合物の物性予測のための原子間距離情報に基づくカーネル設計
        秋田 大空; 馬場 雪乃; 鹿島 久嗣; 世古 敦人
        JSAI大会論文集, Jan. 2018
      • Payload-Based Statistical Intrusion Detection for In-Vehicle Networks.
        Takuya Kuwahara; Yukino Baba; Hisashi Kashima; Takeshi Kishikawa; Jun'ichi Tsurumi; Tomoyuki Haga; Yoshihiro Ujiie; Takamitsu Sasaki; Hideki Matsushima
        Proceedings of the Australasian Workshop on Machine Learning for Cyber-security (co-located with PAKDD 2018), 2018, Peer-reviewed
      • BayesGrad: Explaining Predictions of Graph Convolutional Networks.
        Hirotaka Akita; Kosuke Nakago; Tomoki Komatsu; Yohei Sugawara; Shin-ichi Maeda; Yukino Baba; Hisashi Kashima
        Proceedings of the 25th International Conference on Neural Information Processing (ICONIP), 2018, Peer-reviewed
      • On Reducing Dimensionality of Labeled Data Efficiently.
        Guoxi Zhang; Tomoharu Iwata; Hisashi Kashima
        Advances in Knowledge Discovery and Data Mining - 22nd Pacific-Asia Conference, PAKDD 2018, Melbourne, VIC, Australia, June 3-6, 2018, Proceedings, Part III, 2018, Peer-reviewed
      • Data Analysis Competition Platform for Educational Purposes: Lessons Learned and Future Challenges.
        Yukino Baba; Tomoumi Takase; Kyohei Atarashi; Satoshi Oyama; Hisashi Kashima
        Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, New Orleans, Louisiana, USA, February 2-7, 2018, 2018, Peer-reviewed
      • Supervised and Unsupervised Intrusion Detection Based on CAN Message Frequencies for In-vehicle Network.
        Takuya Kuwahara; Yukino Baba; Hisashi Kashima; Takeshi Kishikawa; Jun'ichi Tsurumi; Tomoyuki Haga; Yoshihiro Ujiie; Takamitsu Sasaki; Hideki Matsushima
        J. Inf. Process., 2018, Peer-reviewed
      • Predictive Modeling of Learning Continuation in Preschool Education Using Temporal Patterns of Development Tests.
        Junpei Naito; Yukino Baba; Hisashi Kashima; Takenori Takaki; Takuya Funo
        Proceedings of the 8th Symposium on Educational Advances in Artificial Intelligence (EAAI), 2018, Peer-reviewed
      • Educational Competition Platform for Data Analysis: Lessons Learned and Future Challenges
        Yukino Baba; Tomoumi Takase; Kyohei Atarashi; Satoshi Oyama; Hisashi Kashima
        Proceedings of the 8th Symposium on Educational Advances in Artificial Intelligence (EAAI), 2018, Peer-reviewed
      • AdaFlock: Adaptive Feature Discovery for Human-in-the-loop Predictive Modeling.
        Ryusuke Takahama; Yukino Baba; Nobuyuki Shimizu; Sumio Fujita; Hisashi Kashima
        Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI),, 2018, Peer-reviewed
      • Quality Control for Crowdsourced Multi-label Classification Using RAkEL.
        Kosuke Yoshimura; Yukino Baba; Hisashi Kashima
        Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2017, Peer-reviewed
      • Using Posters to Recommend Anime and Mangas in a Cold-Start Scenario.
        Jill-Jênn Vie; Florian Yger; Ryan Lahfa; Basile Clement; Kévin Cocchi; Thomas Chalumeau; Hisashi Kashima
        CoRR, 2017, Peer-reviewed
      • Iterative Reduction Worker Filtering for Crowdsourced Label Aggregation.
        Jiyi Li; Hisashi Kashima
        Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2017, Peer-reviewed
      • Autoregressive Tensor Factorization for Spatio-Temporal Predictions.
        Koh Takeuchi; Hisashi Kashima; Naonori Ueda
        Proceedings - IEEE International Conference on Data Mining, ICDM, 2017, Peer-reviewed
      • Using Posters to Recommend Anime and Mangas in a Cold-Start Scenario.
        Jill-Jênn Vie; Florian Yger; Ryan Lahfa; Basile Clement; Kévin Cocchi; Thomas Chalumeau; Hisashi Kashima
        Proceedings of the International Conference on Document Analysis and Recognition, ICDAR, 2017, Peer-reviewed
      • Predicting Fuel Consumption and Flight Delays for Low-Cost Airlines.
        Yuji Horiguchi; Yukino Baba; Hisashi Kashima; Masahito Suzuki; Hiroki Kayahara; Jun Maeno
        Proceedings of the 29th Conference on Innovative Applications of Artificial Intelligence (IAAI), 2017, Peer-reviewed
      • Learning Implicit Tasks for Patient-Specific Risk Modeling in ICU.
        Nozomi Nori; Hisashi Kashima; Kazuto Yamashita; Susumu Kunisawa; Yuichi Imanaka
        Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI), 2017, Peer-reviewed
      • Pairwise HITS: Quality Estimation from Pairwise Comparisons in Creator-Evaluator Crowdsourcing Process.
        Takeru Sunahase; Yukino Baba; Hisashi Kashima
        Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI), 2017, Peer-reviewed
      • A Generalized Model for Multidimensional Intransitivity.
        Jiuding Duan; Jiyi Li; Yukino Baba; Hisashi Kashima
        Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2017, Peer-reviewed
      • Robust Multi-view Topic Modeling by Incorporating Detecting Anomalies.
        Guoxi Zhang; Tomoharu Iwata; Hisashi Kashima
        Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2017, Peer-reviewed
      • Distributed Multi-task Learning for Sensor Network.
        Jiyi Li; Tomohiro Arai; Yukino Baba; Hisashi Kashima; Shotaro Miwa
        Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2017, Peer-reviewed
      • Atomic Distance Kernel for Material Property Prediction.
        Hirotaka Akita; Yukino Baba; Hisashi Kashima; Atsuto Seko
        Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2017, Peer-reviewed
      • Hyper Questions: Unsupervised Targeting of a Few Experts in Crowdsourcing.
        Jiyi Li; Yukino Baba; Hisashi Kashima
        International Conference on Information and Knowledge Management, Proceedings, 2017, Peer-reviewed
      • Koh Takeuchi, Hisashi Kashima, Naonori Ueda
        Koh Takeuchi; Hisashi Kashima; Naonori Ueda
        Proceedings of the 2017 IEEE International Conference on Data Mining (ICDM), 2017, Peer-reviewed
      • Multi-Task Learning for Disease-Specific Risk Modeling of ICU Patients
        Hisashi Kashima
        IEICE Transactions, 2017, Peer-reviewed
      • Link Prediction in Sparse Networks by Incidence Matrix Factorization.
        Sho Yokoi; Hiroshi Kajino; Hisashi Kashima
        J. Inf. Process., 2017, Peer-reviewed
      • Quality control of crowdsourced classification using hierarchical class structures
        Naoki Otani; Yukino Baba; Hisashi Kashima
        EXPERT SYSTEMS WITH APPLICATIONS, Oct. 2016, Peer-reviewed
      • Quality control for crowdsourced enumeration
        Shunsuke Kajimura; Yukino Baba; Hiroshi Kajino; Hisashi Kashima
        Transactions of the Japanese Society for Artificial Intelligence, 18 Feb. 2016, Peer-reviewed
      • Budgeted stream-based active learning via adaptive submodular maximization.
        Kaito Fujii; Hisashi Kashima
        Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016(NIPS), 2016
      • Progressive Comparison for Ranking Estimation.
        Ryusuke Takahama; Toshihiro Kamishima; Hisashi Kashima
        Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence(IJCAI), 2016
      • Participation recommendation system for crowdsourcing contests.
        Yukino Baba; Kei Kinoshita; Hisashi Kashima
        Expert Syst. Appl., 2016, Peer-reviewed
      • Crowdsourcing chart digitizer: task design and quality control for making legacy open data machine-readable.
        Satoshi Oyama; Yukino Baba; Ikki Ohmukai; Hiroaki Dokoshi; Hisashi Kashima
        Int. J. Data Sci. Anal., 2016, Peer-reviewed
      • Learning to Enumerate.
        Patrick Jörger; Yukino Baba; Hisashi Kashima
        ARTIFICIAL NEURAL NETWORKS AND MACHINE LEARNING - ICANN 2016, PT I, 2016, Peer-reviewed
      • Link Prediction by Incidence Matrix Factorization.
        Sho Yokoi; Hiroshi Kajino; Hisashi Kashima
        ECAI 2016: 22ND EUROPEAN CONFERENCE ON ARTIFICIAL INTELLIGENCE, 2016, Peer-reviewed
      • Quality control of crowdsourced classification using hierarchical class structures.
        Naoki Otani; Yukino Baba; Hisashi Kashima
        Expert Syst. Appl., 2016, Peer-reviewed
      • Predicting disease progression from short biomarker series using expert advice algorithm
        Kai Morino; Yoshito Hirata; Ryota Tomioka; Hisashi Kashima; Kenji Yamanishi; Norihiro Hayashi; Shin Egawa; Kazuyuki Aihara
        SCIENTIFIC REPORTS, May 2015, Peer-reviewed
      • Health checkup and telemedical intervention program for preventive medicine in developing countries: verification study.
        Yasunobu Nohara; Eiko Kai; Partha Pratim Ghosh; Rafiqul Islam; Ashir Ahmed; Masahiro Kuroda; Sozo Inoue; Tatsuo Hiramatsu; Michio Kimura; Shuji Shimizu; Kunihisa Kobayashi; Yukino Baba; Hisashi Kashima; Koji Tsuda; Masashi Sugiyama; Mathieu Blondel; Naonori Ueda; Masaru Kitsuregawa; Naoki Nakashima
        Journal of medical Internet research, 28 Jan. 2015, Peer-reviewed
      • Simultaneous higher-order relation prediction via collective incidence matrix embedding
        Nozomi Nori; Danushka Bollegala; Hisashi Kashima
        Transactions of the Japanese Society for Artificial Intelligence, 22 Jan. 2015, Peer-reviewed
      • Regret Lower Bound and Optimal Algorithm in Dueling Bandit Problem.
        Junpei Komiyama; Junya Honda; Hisashi Kashima; Hiroshi Nakagawa
        CoRR, 2015
      • Simultaneous Modeling of Multiple Diseases for Mortality Prediction in Acute Hospital Care.
        Nozomi Nori; Hisashi Kashima; Kazuto Yamashita; Hiroshi Ikai; Yuichi Imanaka
        Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015, Peer-reviewed
      • Regret Lower Bound and Optimal Algorithm in Dueling Bandit Problem.
        Junpei Komiyama; Junya Honda; Hisashi Kashima; Hiroshi Nakagawa
        Proceedings of The 28th Conference on Learning Theory(COLT), 2015, Peer-reviewed
      • Quality Control for Crowdsourced POI Collection.
        Shunsuke Kajimura; Yukino Baba; Hiroshi Kajino; Hisashi Kashima
        Proceedings of the 19th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2015, Peer-reviewed
      • Predictive Approaches for Low-Cost Preventive Medicine Program in Developing Countries.
        Yukino Baba; Hisashi Kashima; Yasunobu Nohara; Eiko Kai; Partha Pratim Ghosh; Rafiqul Islam Maruf; Ashir Ahmed; Masahiro Kuroda; Sozo Inoue; Tatsuo Hiramatsu; Michio Kimura; Shuji Shimizu; Kunihisa Kobayashi; Koji Tsuda; Masashi Sugiyama; Mathieu Blondel; Naonori Ueda; Masaru Kitsuregawa; Naoki Nakashima
        Proceedings of the 21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2015, Peer-reviewed
      • Quality Control for Crowdsourced Hierarchical Classification.
        Naoki Otani; Yukino Baba; Hisashi Kashima
        Proceedings of the 2015 IEEE International Conference on Data Mining (ICDM), 2015, Peer-reviewed
      • From one star to three stars: Upgrading legacy open data using crowdsourcing.
        Satoshi Oyama; Yukino Baba; Ikki Ohmukai; Hiroaki Dokoshi; Hisashi Kashima
        2015 IEEE International Conference on Data Science and Advanced Analytics, DSAA 2015, Campus des Cordeliers, Paris, France, October 19-21, 2015, 2015, Peer-reviewed
      • Quantum Energy Prediction Using Graph Kernel.
        Jiuding Duan; Atsuto Seko; Hisashi Kashima
        2015 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC 2015): BIG DATA ANALYTICS FOR HUMAN-CENTRIC SYSTEMS, 2015, Peer-reviewed
      • Tensor Decomposition via Convex Optimization
        Tomioka Ryota; Suzuki Taiji; Hayashi Kohei; Kashima Hisashi
        Bulletin of the Japan Society for Industrial and Applied Mathematics, 2014
      • A Label Completion Approach to Crowd Approximation.
        Toshihiro Watanabe; Hisashi Kashima
        Neural Information Processing - 21st International Conference, 2014
      • Crowdsourced Data Analytics: A Case Study of a Predictive Modeling Competition.
        Yukino Baba; Nozomi Nori; Shigeru Saito; Hisashi Kashima
        Proceedings of the Seconf AAAI Conference on Human Computation and Crowdsourcing(HCOMP), 2014
      • A dimension reduction approach to multinomial relation prediction
        Nozomi Nori; Danushka Bollegala; Hisashi Kashima
        Transactions of the Japanese Society for Artificial Intelligence, 2014, Peer-reviewed
      • Quality Control for Crowdsourced Enumeration Tasks.
        Shunsuke Kajimura; Yukino Baba; Hiroshi Kajino; Hisashi Kashima
        Transactions of the Japanese Society for Artificial Intelligence, 2014, Peer-reviewed
      • Latent Confusion Analysis by Normalized Gamma Construction.
        Issei Sato; Hisashi Kashima; Hiroshi Nakagawa
        In Proceedings of the 31st International Conference on Machine Learning (ICML 2014), 2014, Peer-reviewed
      • マルチタスク学習を用いた複数物性値の同時予測 (情報論的学習理論と機械学習)
        岩瀬 智亮; 世古 敦人; 鹿島 久嗣
        電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, Jan. 2014
      • Crowdsourced data analytics: A case study of a predictive modeling competition.
        Yukino Baba; Nozomi Nori; Shigeru Saito; Hisashi Kashima
        Proceedings of the 2014 International Conference on Data Science and Advanced Analytics (DSAA), 2014, Peer-reviewed
      • Instance-Privacy Preserving Crowdsourcing.
        Hiroshi Kajino; Yukino Baba; Hisashi Kashima
        Proceedings of the 2nd AAAI Conference on Human Computation and Crowdsourcing (HCOMP), 2014, Peer-reviewed
      • ヒューマンコンピュテーション概説
        鹿島, 久嗣; 馬場, 雪乃
        人工知能, Jan. 2014
      • Crowdordering.
        Toshiko Matsui; Yukino Baba; Toshihiro Kamishima; Hisashi Kashima
        Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2014, Peer-reviewed
      • Learning an accurate entity resolution model from crowdsourced labels.
        Jingjing Wang; Satoshi Oyama; Masahito Kurihara; Hisashi Kashima
        Proceedings of the 8th International Conference on Ubiquitous Information Management and Communication, ICUIMC 2014, 2014, Peer-reviewed
      • Leveraging non-expert crowdsourcing workers for improper task detection in crowdsourcing marketplaces.
        Yukino Baba; Hisashi Kashima; Kei Kinoshita; Goushi Yamaguchi; Yosuke Akiyoshi
        Expert Syst. Appl., 2014, Peer-reviewed
      • Preserving worker privacy in crowdsourcing.
        Hiroshi Kajino; Hiromi Arai; Hisashi Kashima
        Data Min. Knowl. Discov., 2014, Peer-reviewed
      • Matrix Factorization With Aggregated Observations.
        Yoshifumi Aimoto; Hisashi Kashima
        Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2013, Peer-reviewed
      • Statistical quality estimation for general crowdsourcing tasks.
        Yukino Baba; Hisashi Kashima
        The 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2013, Chicago, IL, USA, August 11-14, 2013, 2013, Peer-reviewed
      • Accurate Integration of Crowdsourced Labels Using Workers' Self-reported Confidence Scores.
        Satoshi Oyama; Yukino Baba; Yuko Sakurai; Hisashi Kashima
        IJCAI 2013, Proceedings of the 23rd International Joint Conference on Artificial Intelligence, Beijing, China, August 3-9, 2013, 2013, Peer-reviewed
      • Leveraging Crowdsourcing to Detect Improper Tasks in Crowdsourcing Marketplaces.
        Yukino Baba; Hisashi Kashima; Kei Kinoshita; Goushi Yamaguchi; Yosuke Akiyoshi
        Proceedings of the Twenty-Fifth Innovative Applications of Artificial Intelligence Conference, IAAI 2013, July 14-18, 2013, Bellevue, Washington, USA., 2013, Peer-reviewed
      • EM-Based Inference of True Labels Using Confidence Judgments.
        Satoshi Oyama; Yukino Baba; Yuko Sakurai; Hisashi Kashima
        Human Computation and Crowdsourcing: Works in Progress and Demonstration Abstracts, An Adjunct to the Proceedings of the First AAAI Conference on Human Computation and Crowdsourcing, November 7-9, 2013, Palm Springs, CA, USA, 2013, Peer-reviewed
      • Crowdsourcing Quality Control for Item Ordering Tasks.
        Toshiko Matsui; Yukino Baba; Toshihiro Kamishima; Hisashi Kashima
        Human Computation and Crowdsourcing: Works in Progress and Demonstration Abstracts, An Adjunct to the Proceedings of the First AAAI Conference on Human Computation and Crowdsourcing, November 7-9, 2013, Palm Springs, CA, USA, 2013, Peer-reviewed
      • Statistical Quality Estimation for General Crowdsourcing Tasks.
        Yukino Baba; Hisashi Kashima
        Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013, Peer-reviewed
      • Clustering Crowds.
        Hiroshi Kajino; Yuta Tsuboi; Hisashi Kashima
        Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence, July 14-18, 2013, Bellevue, Washington, USA., 2013, Peer-reviewed
      • Large-Scale Personalized Human Activity Recognition Using Online Multitask Learning.
        Xu Sun 0001; Hisashi Kashima; Naonori Ueda
        IEEE Trans. Knowl. Data Eng., 2013, Peer-reviewed
      • Fast Iterative Mining Using Sparsity-Inducing Loss Functions.
        Hiroto Saigo; Hisashi Kashima; Koji Tsuda
        IEICE Trans. Inf. Syst., 2013, Peer-reviewed
      • Fast Computation of Subpath Kernel for Trees
        Daisuke Kimura; Hisashi Kashima
        CoRR, 2012
      • Pattern Recognition in Bioinformatics - 7th IAPR International Conference, PRIB 2012, Tokyo, Japan, November 8-10, 2012. Proceedings
        PRIB, 2012
      • Fast Computation of Subpath Kernel for Trees.
        Daisuke Kimura; Hisashi Kashima
        Proceedings of the 29th International Conference on Machine Learning(ICML), 2012
      • Fast Similarity Computation in Factorized Tensors.
        Michael E. Houle; Hisashi Kashima; Michael Nett
        Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2012, Peer-reviewed
      • Parametric Return Density Estimation for Reinforcement Learning
        Tetsuro Morimura; Masashi Sugiyama; Hisashi Kashima; Hirotaka Hachiya; Toshiyuki Tanaka
        CoRR, 2012, Peer-reviewed
      • Convex formulations of learning from crowds
        Hiroshi Kajino; Hisashi Kashima
        Transactions of the Japanese Society for Artificial Intelligence, 2012
      • Self-measuring similarity for multi-task Gaussian process
        Kohei Hayashi; Takashi Takenouchi; Ryota Tomioka; Hisashi Kashima
        Transactions of the Japanese Society for Artificial Intelligence, 2012
      • Learning from Crowds and Experts.
        Hiroshi Kajino; Yuta Tsuboi; Issei Sato; Hisashi Kashima
        Transactions of the Japanese Society for Artificial Intelligence, 2012, Peer-reviewed
      • Hash-based structural similarity for semi-supervised Learning on attribute graphs.
        Shohei Hido; Hisashi Kashima
        2012 21ST INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR 2012), 2012, Peer-reviewed
      • Self-measuring Similarity for Multi-task Gaussian Process.
        Kohei Hayashi; Takashi Takenouchi; Ryota Tomioka; Hisashi Kashima
        Unsupervised and Transfer Learning - Workshop held at ICML 2011, Bellevue, Washington, USA, July 2, 2011, 2012, Peer-reviewed
      • Generalized Expansion Dimension.
        Michael E. Houle; Hisashi Kashima; Michael Nett
        12TH IEEE INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOPS (ICDMW 2012), 2012, Peer-reviewed
      • Multinomial Relation Prediction in Social Data: A Dimension Reduction Approach.
        Nozomi Nori; Danushka Bollegala; Hisashi Kashima
        Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, July 22-26, 2012, Toronto, Ontario, Canada., 2012, Peer-reviewed
      • A Convex Formulation for Learning from Crowds.
        Hiroshi Kajino; Yuta Tsuboi; Hisashi Kashima
        Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, July 22-26, 2012, Toronto, Ontario, Canada., 2012, Peer-reviewed
      • Link Prediction Across Time via Cross-Temporal Locality Preserving Projections.
        Satoshi Oyama; Kohei Hayashi; Hisashi Kashima
        IEICE Trans. Inf. Syst., 2012, Peer-reviewed
      • Machine learning approach for finding business partners and building reciprocal relationships.
        Junichiro Mori; Yuya Kajikawa; Hisashi Kashima; Ichiro Sakata
        Expert Syst. Appl., 2012, Peer-reviewed
      • Tensor factorization using auxiliary information.
        Atsuhiro Narita; Kohei Hayashi; Ryota Tomioka; Hisashi Kashima
        Data Min. Knowl. Discov., 2012, Peer-reviewed
      • A New Multi-task Learning Method for Personalized Activity Recognition.
        Xu Sun 0001; Hisashi Kashima; Ryota Tomioka; Naonori Ueda; Ping Li 0001
        Proceedings - IEEE International Conference on Data Mining, ICDM, 2011, Peer-reviewed
      • Finding business partners and building reciprocal relationships - A machine learning approach
        Junichiro Mori; Yuya Kajikawa; Hisashi Kashima
        Proceedings of the 1st International Technology Management Conference, ITMC 2011, 2011, Peer-reviewed
      • A subpath kernel for rooted unordered trees
        Daisuke Kimura; Tetsuji Kuboyama; Tetsuo Shibuya; Hisashi Kashima
        Transactions of the Japanese Society for Artificial Intelligence, 2011
      • Large Scale Real-Life Action Recognition Using Conditional Random Fields with Stochastic Training.
        Xu Sun 0001; Hisashi Kashima; Ryota Tomioka; Naonori Ueda
        ADVANCES IN KNOWLEDGE DISCOVERY AND DATA MINING, PT II, 2011, Peer-reviewed
      • Tensor Factorization Using Auxiliary Information.
        Atsuhiro Narita; Kohei Hayashi; Ryota Tomioka; Hisashi Kashima
        MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES, PT II, 2011, Peer-reviewed
      • Statistical Performance of Convex Tensor Decomposition.
        Ryota Tomioka; Taiji Suzuki; Kohei Hayashi; Hisashi Kashima
        Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, Granada, Spain., 2011, Peer-reviewed
      • Fast Newton-CG Method for Batch Learning of Conditional Random Fields.
        Yuta Tsuboi; Yuya Unno; Hisashi Kashima; Naoaki Okazaki
        Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence(AAAI), 2011, Peer-reviewed
      • A Subpath Kernel for Rooted Unordered Trees.
        Daisuke Kimura; Tetsuji Kuboyama; Tetsuo Shibuya; Hisashi Kashima
        Advances in Knowledge Discovery and Data Mining - 15th Pacific-Asia Conference, PAKDD 2011, Shenzhen, China, May 24-27, 2011, Proceedings, Part I, 2011, Peer-reviewed
      • Cross-Temporal Link Prediction.
        Satoshi Oyama; Kohei Hayashi; Hisashi Kashima
        11th IEEE International Conference on Data Mining, ICDM 2011, Vancouver, BC, Canada, December 11-14, 2011, 2011, Peer-reviewed
      • Prediction of protein-ligand binding affinities using multiple instance learning
        Reiji Teramoto; Hisashi Kashima
        JOURNAL OF MOLECULAR GRAPHICS & MODELLING, Nov. 2010, Peer-reviewed
      • Least absolute policy iteration - A robust approach to value function approximation
        Masashi Sugiyama; Hirotaka Hachiya; Hisashi Kashima; Tetsuro Mortmura
        IEICE Transactions on Information and Systems, Sep. 2010, Peer-reviewed
      • Simultaneous Prediction of Biological Networks of Multiple Species from Genome-wide Data and Evolutionary Information: A Semi-supervised Approach
        Hisashi Kashima; Tsuyoshi Kato; Yoshihiro Yamanishi; Masashi Sugiyama; Koji Tsuda
        IEEE Transactions on Knowledge and Data Enginieering, Jul. 2010, Peer-reviewed
      • Unsupervised Change Analysis Using Supervised Learning
        MATSUZAWA Hirofumi; HIDO Shohei; IDE Tsuyoshi; KASHIMA Hisashi
        The IEICE transactions on information and systems (Japanese edetion), 01 Jun. 2010
      • Parametric Return Density Estimation for Reinforcement Learning.
        Tetsuro Morimura; Masashi Sugiyama; Hisashi Kashima; Hirotaka Hachiya; Toshiyuki Tanaka
        UAI 2010(UAI), 2010
      • Graph kernels for chemoinformatics
        Hisashi Kashima; Hiroto Saigo; Masahiro Hattori; Koji Tsuda
        Chemoinformatics and Advanced Machine Learning Perspectives: Complex Computational Methods and Collaborative Techniques, 2010, Peer-reviewed
      • Prediction of compound-protein interactions with machine learning methods
        Yoshihiro Yamanishi; Hisashi Kashima
        Chemoinformatics and Advanced Machine Learning Perspectives: Complex Computational Methods and Collaborative Techniques, 2010, Peer-reviewed
      • Predicting customer-supplier relationships using network-based features
        J. Mori; Y. Kajikawa; I. Sakata; H. Kashima
        IEEM2010 - IEEE International Conference on Industrial Engineering and Engineering Management, 2010, Peer-reviewed
      • Nonparametric Return Distribution Approximation for Reinforcement Learning.
        Tetsuro Morimura; Masashi Sugiyama; Hisashi Kashima; Hirotaka Hachiya; Toshiyuki Tanaka
        ICML 2010 - Proceedings, 27th International Conference on Machine Learning, 2010, Peer-reviewed
      • A Fast Augmented Lagrangian Algorithm for Learning Low-Rank Matrices.
        Ryota Tomioka; Taiji Suzuki; Masashi Sugiyama; Hisashi Kashima
        ICML 2010 - Proceedings, 27th International Conference on Machine Learning, 2010, Peer-reviewed
      • Finding Itemset-Sharing Patterns in a Large Itemset-Associated Graph.
        Mutsumi Fukuzaki; Mio Seki; Hisashi Kashima; Jun Sese
        ADVANCES IN KNOWLEDGE DISCOVERY AND DATA MINING, PT II, PROCEEDINGS, 2010, Peer-reviewed
      • Least Absolute Policy Iteration-A Robust Approach to Value Function Approximation.
        Masashi Sugiyama; Hirotaka Hachiya; Hisashi Kashima; Tetsuro Morimura
        IEICE Trans. Inf. Syst., 2010, Peer-reviewed
      • A Transfer Learning Approach and Selective Integration of Multiple Types of Assays for Biological Network Inference.
        Tsuyoshi Kato; Kinya Okada; Hisashi Kashima; Masashi Sugiyama
        Int. J. Knowl. Discov. Bioinform., 2010, Peer-reviewed
      • Conic Programming for Multitask Learning.
        Tsuyoshi Kato; Hisashi Kashima; Masashi Sugiyama; Kiyoshi Asai
        IEEE Trans. Knowl. Data Eng., 2010, Peer-reviewed
      • Fast and Scalable Algorithms for Semi-supervised Link Prediction on Static and Dynamic Graphs.
        Rudy Raymond; Hisashi Kashima
        MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES, PT III, 2010, Peer-reviewed
      • Averaged Stochastic Gradient Descent with Feedback: An Accurate, Robust, and Fast Training Method.
        Xu Sun 0001; Hisashi Kashima; Takuya Matsuzaki; Naonori Ueda
        Proc. 10th International Conference on Data Mining, 2010, Peer-reviewed
      • Cartesian Kernel: An Efficient Alternative to the Pairwise Kernel.
        Hisashi Kashima; Satoshi Oyama; Yoshihiro Yamanishi; Koji Tsuda
        IEICE Trans. Inf. Syst., 2010, Peer-reviewed
      • Reaction graph kernels predict EC numbers of unknown enzymatic reactions in plant secondary metabolism.
        Hiroto Saigo; Masahiro Hattori; Hisashi Kashima; Koji Tsuda
        BMC Bioinform., 2010, Peer-reviewed
      • Protein complex prediction via verifying and reconstructing the topology of domain-domain interactions.
        Yosuke Ozawa; Rintaro Saito; Shigeo Fujimori; Hisashi Kashima; Masamichi Ishizaka; Hiroshi Yanagawa; Etsuko Miyamoto-Sato; Masaru Tomita
        BMC Bioinform., 2010, Peer-reviewed
      • 日本語単語分割の分野適応のための部分的アノテーションを用いた条件付き確率場の学習
        坪井祐太; 森信介; 鹿島久嗣; 小田裕樹; 松本裕治
        情報処理学会論文誌ジャーナル(CD-ROM), 15 Jun. 2009
      • Side Effect Prediction Using Cooperative Pathways.
        Mutsumi Fukuzaki; Mio Seki; Hisashi Kashima; Jun Sese
        2009 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2009, 2009, Peer-reviewed
      • A Linear-Time Graph Kernel.
        Shohei Hido; Hisashi Kashima
        2009 9TH IEEE INTERNATIONAL CONFERENCE ON DATA MINING, 2009, Peer-reviewed
      • Least absolute policy iteration for robust value function approximation.
        Masashi Sugiyama; Hirotaka Hachiya; Hisashi Kashima; Tetsuro Morimura
        ICRA: 2009 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, VOLS 1-7, 2009, Peer-reviewed
      • Robust Label Propagation on Multiple Networks.
        Tsuyoshi Kato; Hisashi Kashima; Masashi Sugiyama
        IEEE Trans. Neural Networks, 2009, Peer-reviewed
      • Direct Density Ratio Estimation for Large-scale Covariate Shift Adaptation.
        Yuta Tsuboi; Hisashi Kashima; Shohei Hido; Steffen Bickel; Masashi Sugiyama
        J. Inf. Process., 2009, Peer-reviewed
      • Training Conditional Random Fields Using Partial Annotations for Domain Adaptation of Japanese Word Segmentation
        Yuta Tsuboi; Shinsuke Mori; Hisashi Kashima; Hiroki Oda; Yuji Matsumoto
        IPSJ Journal, 2009, Peer-reviewed
      • Roughly balanced bagging for imbalanced data.
        Shohei Hido; Hisashi Kashima; Yutaka Takahashi 0001
        Stat. Anal. Data Min., 2009, Peer-reviewed
      • Recent Advances and Trends in Large-Scale Kernel Methods.
        Hisashi Kashima; Tsuyoshi Idé; Tsuyoshi Kato; Masashi Sugiyama
        IEICE Trans. Inf. Syst., 2009, Peer-reviewed
      • Link Propagation: A Fast Semi-supervised Learning Algorithm for Link Prediction.
        Hisashi Kashima; Tsuyoshi Kato; Yoshihiro Yamanishi; Masashi Sugiyama; Koji Tsuda
        Proceedings of the SIAM International Conference on Data Mining, SDM 2009, April 30 - May 2, 2009, Sparks, Nevada, USA, 2009, Peer-reviewed
      • On Pairwise Kernels: An Efficient Alternative and Generalization Analysis.
        Hisashi Kashima; Satoshi Oyama; Yoshihiro Yamanishi; Koji Tsuda
        ADVANCES IN KNOWLEDGE DISCOVERY AND DATA MINING, PROCEEDINGS, 2009, Peer-reviewed
      • Simultaneous inference of biological networks of multiple species from genome-wide data and evolutionary information: a semi-supervised approach.
        Hisashi Kashima; Yoshihiro Yamanishi; Tsuyoshi Kato; Masashi Sugiyama; Koji Tsuda
        Bioinform., 2009, Peer-reviewed
      • Direct importance estimation for covariate shift adaptation
        Masashi Sugiyama; Taiji Suzuki; Shinichi Nakajima; Hisashi Kashima; Paul von Buenau; Motoaki Kawanabe
        ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS, Dec. 2008, Peer-reviewed
      • Roughly Balanced Bagging for Imbalanced Data.
        Shohei Hido; Hisashi Kashima
        Proceedings of the SIAM International Conference on Data Mining(SDM), 2008
      • Training Conditional Random Fields Using Incomplete Annotations.
        Yuta Tsuboi; Hisashi Kashima; Shinsuke Mori; Hiroki Oda; Yuji Matsumoto 0001
        COLING 2008(COLING), 2008
      • Direct Density Ratio Estimation for Large-scale Covariate Shift Adaptation.
        Yuta Tsuboi; Hisashi Kashima; Shohei Hido; Steffen Bickel; Masashi Sugiyama
        Society for Industrial and Applied Mathematics - 8th SIAM International Conference on Data Mining 2008, Proceedings in Applied Mathematics 130, 2008, Peer-reviewed
      • K-means clustering of proportional data using L1 distance.
        Hisashi Kashima; Jianying Hu; Bonnie K. Ray; Moninder Singh
        19TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOLS 1-6, 2008, Peer-reviewed
      • Unsupervised Change Analysis Using Supervised Learning.
        Shohei Hido; Tsuyoshi Idé; Hisashi Kashima; Harunobu Kubo; Hirofumi Matsuzawa
        ADVANCES IN KNOWLEDGE DISCOVERY AND DATA MINING, PROCEEDINGS, 2008, Peer-reviewed
      • Regression with interval output values.
        Hisashi Kashima; Kazutaka Yamasaki; Akihiro Inokuchi; Hiroto Saigo
        19TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOLS 1-6, 2008, Peer-reviewed
      • A new objective function for sequence labeling.
        Yuta Tsuboi; Hisashi Kashima
        19TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOLS 1-6, 2008, Peer-reviewed
      • Integration of Multiple Networks for Robust Label Propagation.
        Tsuyoshi Kato; Hisashi Kashima; Masashi Sugiyama
        Proceedings of the SIAM International Conference on Data Mining, SDM 2008, April 24-26, 2008, Atlanta, Georgia, USA, 2008, Peer-reviewed
      • Inlier-Based Outlier Detection via Direct Density Ratio Estimation.
        Shohei Hido; Yuta Tsuboi; Hisashi Kashima; Masashi Sugiyama; Takafumi Kanamori
        ICDM 2008: EIGHTH IEEE INTERNATIONAL CONFERENCE ON DATA MINING, PROCEEDINGS, 2008, Peer-reviewed
      • Training Conditional Random Fields using Partial and Ambiguous Structured Labels
        TSUBOI YUTA; KASHIMA HISASHI; MORI SHINSUKE; ODA HIROKI; MATSUMOTO YUJI
        IPSJ SIG Notes, 19 Nov. 2007
      • A spectrum tree kernel
        Tetsuji Kuboyama; Kouichi Hirata; Hisashi Kashima; Kiyoko F. Aoki-Kinoshita; Hiroshi Yasuda
        Transactions of the Japanese Society for Artificial Intelligence, 2007, Peer-reviewed
      • Risk-Sensitive Learning via Minimization of Empirical Conditional Value-at-Risk.
        Hisashi Kashima
        IEICE Trans. Inf. Syst., 2007, Peer-reviewed
      • Direct Importance Estimation with Model Selection and Its Application to Covariate Shift Adaptation.
        Masashi Sugiyama; Shinichi Nakajima; Hisashi Kashima; Paul von Bünau; Motoaki Kawanabe
        Advances in Neural Information Processing Systems 20, Proceedings of the Twenty-First Annual Conference on Neural Information Processing Systems, Vancouver, British Columbia, Canada, December 3-6, 2007, 2007, Peer-reviewed
      • Multi-Task Learning via Conic Programming.
        Tsuyoshi Kato; Hisashi Kashima; Masashi Sugiyama; Kiyoshi Asai
        Advances in Neural Information Processing Systems 20, Proceedings of the Twenty-First Annual Conference on Neural Information Processing Systems, Vancouver, British Columbia, Canada, December 3-6, 2007, 2007, Peer-reviewed
      • Design and analysis of convolution kernels for tree-structured data
        Hisashi Kashima; Hiroshi Sakamoto; Teruo Koyanagi
        Transactions of the Japanese Society for Artificial Intelligence, 2006, Peer-reviewed
      • Risk-Sensitive Learning via Expected Shortfall Minimization.
        Hisashi Kashima
        PROCEEDINGS OF THE SIXTH SIAM INTERNATIONAL CONFERENCE ON DATA MINING, 2006, Peer-reviewed
      • Network-Based Problem Detection for Distributed Systems
        Hisashi Kashima; Tadashi Tsumura; Tsuyoshi Ide; Takahide Nogayama; Ryo Hirade; Hiroaki Etoh; Takeshi Fukuda
        IEICE Transaction, 2006, Peer-reviewed
      • A Parameterized Probabilistic Model of Network Evolution for Supervised Link Prediction.
        Hisashi Kashima; Naoki Abe
        Transactions of the Japanese Society for Artificial Intelligence, 2006, Peer-reviewed
      • A gram distribution kernel applied to glycan classification and motif extraction.
        Kuboyama T; Hirata K; Aoki-Kinoshita KF; Kashima H; Yasuda H
        Genome informatics. International Conference on Genome Informatics, 2006, Peer-reviewed
      • Network-Based Problem Detection for Distributed Systems.
        Hisashi Kashima; Tadashi Tsumura; Tsuyoshi Idé; Takahide Nogayama; Ryo Hirade; Hiroaki Etoh; Takeshi Fukuda
        Proceedings - International Conference on Data Engineering, 2005, Peer-reviewed
      • Eigenspace-based anomaly detection in computer systems.
        Tsuyoshi Idé; Hisashi Kashima
        Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining(KDD), 2004
      • Kernel-based discriminative learning algorithms for labeling sequences, trees, and graphs.
        Hisashi Kashima; Yuta Tsuboi
        Machine Learning(ICML), 2004
      • Effective Dimension in Anomaly Detection: Its Application to Computer Systems.
        Tsuyoshi Idé; Hisashi Kashima
        NEW FRONTIERS IN ARTIFICIAL INTELLIGENCE, 2004, Peer-reviewed
      • Efficient filtering methods for clustering cDNAs with spliced sequence alignment.
        Tetsuo Shibuya; Hisashi Kashima; Akihiko Konagaya
        Bioinform., 2004, Peer-reviewed
      • Marginalized Kernels Between Labeled Graphs.
        Hisashi Kashima; Koji Tsuda; Akihiro Inokuchi
        Machine Learning(ICML), 2003
      • Mining Significant Pairs of Patterns from Graph Structures with Class Labels.
        Akihiro Inokuchi; Hisashi Kashima
        Proceedings of the 3rd IEEE International Conference on Data Mining (ICDM 2003)(ICDM), 2003
      • Kernels for Semi-Structured Data.
        Hisashi Kashima; Teruo Koyanagi
        Machine Learning(ICML), 2002

      Misc.

      • Cost-sensitive NO-SHOW prediction for airline companies
        堀口 裕士; 馬場 雪乃; 鹿島 久嗣; 小島 武; 栢原 宏樹; 前野 純
        電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 18 Sep. 2017
      • OS-20 ヒューマンコンピュテーションとクラウドソーシング(オーガナイズドセッション,<特集>2015年度人工知能学会全国大会(第29回))
        馬場 雪乃; 芦川 将之; 鹿島 久嗣; 京都大学; 株式会社東芝研究開発センター; 京都大学
        人工知能 = journal of the Japanese Society for Artificial Intelligence, 01 Nov. 2015
      • Machine Learning Approaches for Structured Data(Learning and Discovery, Doctorial Theses on Aritifical Intelligence)
        鹿島 久嗣; 京都大学大学院情報学研究科
        人工知能学会誌 = Journal of Japanese Society for Artificial Intelligence, 01 Jan. 2008
      • ネットワーク構造予測
        鹿島久嗣
        人工知能学会誌, 2007
      • Kernel Methods for Mining Structured Data
        鹿島 久嗣
        情報処理, 15 Jan. 2005
      • 複数生物種ネットワークの同時予測 : 半教師つき学習によるアプローチ—Simultaneous Inference of Multiple Biological Networks—バイオ情報学(BIO) Vol.2010-BIO-21
        鹿島 久嗣; 山西 芳裕; 加藤 毅
        情報処理学会研究報告, Aug. 2010
      • Link Prediction in Chemical Compound Network Under Observation Bias
        乾拓海; 原田将之介; LIU Yang; 竹内孝; 瀧川一学; 山西芳裕; 鹿島久嗣
        人工知能学会全国大会(Web), 2022
      • A Linear Time Subpath Kernel for Unordered Trees
        木村 大翼; 鹿島 久嗣
        人工知能学会全国大会論文集, 2012
      • Predicting User Actions in Social Web Services: A Dimension Reduction Approach
        則 のぞみ; ボレガラ ダヌシカ; 鹿島 久嗣
        人工知能学会全国大会論文集, 2012
      • Eigenspace Approach to Anomaly Detection of Computer Systems
        井手 剛; 鹿島 久嗣
        人工知能学会全国大会論文集, 2004
      • Kernel-based Discriminative Learning Algorithms for Labeling Structured Data
        KASHIMA Hisashi; TSUBOI Yuta
        IEICE technical report. Artificial intelligence and knowledge-based processing, 14 Jun. 2004
      • Accurate cDNA Clustering Algorithm based on Spliced Sequence Alignment
        SHIBUYA Tetsuo; SCHONBACH Christian; KASHIMA Hisashi; KONAGAYA Akihiko
        IEICE technical report. Theoretical foundations of Computing, 17 May 2002
      • Optimal Winner Determination Algorithms for E-procurement Auction
        KASHIMA Hisashi; KAJINAGA Yasumasa
        IEICE technical report. Theoretical foundations of Computing, 27 Nov. 2000
      • Kernel Methods for Analyzing Structured Data
        KASHIMA Hisashi
        IEICE technical report. Natural language understanding and models of communication, 25 Feb. 2005
      • Machine Learning Methods for Graphs and Networks
        KASHIMA Hisashi
        IPSJ Magazine, 15 Jul. 2009
      • Direct Density Ratio Estimation for Large-scale Covariate Shift Adaptation
        Yuta Tsuboi; Hisashi Kashima; Shohei Hido; Steffen Bickel; Masashi Sugiyama
        IPSJ J., 15 Apr. 2009
      • Quality Control in Human-Machine Hybrid Crowdsourcing
        WATANABE Toshihiro; ITOKO Toshinari; SAITO Shin; KOBAYASHI Masatomo; TAKAGI Hironobu; KASHIMA Hisashi
        電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 05 Mar. 2015
      • クラウドソーシングを用いた同一性判定のための機械学習方式
        王晶晶; 小山聡; 栗原正仁; 鹿島久嗣
        第75回全国大会講演論文集, 06 Mar. 2013
      • A Generalized Model for Multidimensional Intransitivity (情報論的学習理論と機械学習) -- (情報論的学習理論ワークショップ(IBIS2016))
        Duan Jiuding; Li Jiyi; Baba Yukino; Kashima Hisashi
        電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 16 Nov. 2016
      • Disease-Dependent Mortality Prediction in ICU by Multi-Task Learning
        則 のぞみ; 鹿島 久嗣; 山下 和人
        人工知能学会全国大会論文集, 2015
      • Relation Prediction Using Incidence Matrix Decomposition
        横井 祥; 梶野 洸; 鹿島 久嗣
        人工知能学会全国大会論文集, 2015
      • Winning Prediction for Crowdsourcing Contests
        馬場 雪乃; 木下 慶; 鹿島 久嗣
        人工知能学会全国大会論文集, 2015
      • A Method of Quality Control for Crowdsourced POI Collection
        梶村 俊介; 馬場 雪乃; 鹿島 久嗣
        人工知能学会全国大会論文集, 2014
      • Higher-order Relation Prediction on Multi-relational Network by Hypergraph Incidence Matrix Factorization
        則 のぞみ; ボレガラ ダヌシカ; 鹿島 久嗣
        人工知能学会全国大会論文集, 2014
      • Fast and Memory-Efficient Kernel Learning for Trees with Succinct Data Structures
        木村 大翼; 鹿島 久嗣
        人工知能学会全国大会論文集, 2013
      • Direct Density Ratio Estimation for Large-scale Covariate Shift Adaptation
        TSUBOI YUTA; KASHIMA HISASHI; HIDO SHOHEI
        情報処理学会論文誌 論文誌ジャーナル, Apr. 2009
      • Dual Convolutional Neural Network for Graph of Graphs Link Prediction.
        Shonosuke Harada; Hirotaka Akita; Masashi Tsubaki; Yukino Baba; Ichigaku Takigawa; Yoshihiro Yamanishi; Hisashi Kashima
        CoRR, 2018
      • OS-18 ヒューマンコンピュテーションとクラウドソーシング(オーガナイズドセッション,<特集>2014年度人工知能学会全国大会(第28回))
        小山 聡; 鹿島 久嗣; 櫻井 祐子; 馬場 雪乃; 松原 繁夫
        人工知能 = journal of the Japanese Society for Artificial Intelligence, 01 Nov. 2014
      • On Improvement of Tensor Spectral Method for Estimation of Mixed Membership Stochastic Block Model
        KAIGAISHI Wataru; KASHIMA Hisashi
        Technical report of IEICE. PRMU, 01 Sep. 2014
      • Crowdsourcing and Big Data Analysis
        KASHIMA HISASHI
        Technical report of IEICE. PRMU, 25 Aug. 2014
      • Crowdsourcing and Big Data Analysis
        Hisashi Kashima
        IPSJ SIG Notes. CVIM, 25 Aug. 2014
      • On Improvement of Tensor Spectral Method for Estimation of Mixed Membership Stochastic Block Model
        Wataru Kaigaishi; Hisashi Kashima
        IPSJ SIG Notes. CVIM, 25 Aug. 2014
      • Making Legacy Open Data Machine Readable by Crowdsourcing
        OYAMA Satoshi; BABA Yukino; OHMUKAI Ikki; DOKOSHI Hiroaki; KASHIMA Hisashi
        IEICE technical report. SC, Services Computing, 20 Aug. 2014
      • Crowdsourcing for Big Data Analytics
        KASHIMA Hisashi
        The Journal of the Institute of Electronics, Information, and Communication Engineers, May 2014
      • Focused Tensor Completion
        AKAMA Taketo; BABA Yukino; KASHIMA Hisashi
        電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 06 Mar. 2014
      • Editors' Introduction to "Human Computation and Crowdsourcing"(Human Computation and Crowdsourcing)
        PTASZYNSKI Michal; RZEPKA Rafal; OYAMA Satoshi; KURIHARA Masahito; Satoshi Oyama; Hisashi Kashima; Yuko Sakuraia; Shigeo Matsubara
        Computer Software, 01 Jan. 2014
      • OS-07 ヒューマンコンピュテーションとクラウドソーシング(オーガナイズドセッション,<特集>2013年度人工知能学会全国大会(第27回))
        小山 聡; 鹿島 久嗣; 櫻井 祐子; 松原 繁夫
        人工知能学会誌 = Journal of Japanese Society for Artificial Intelligence, 01 Nov. 2013
      • A Simultaneous Completion Method for Multiple Relational Data
        IEIRI Yutaka; KASHIMA Hisashi
        電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 18 Jul. 2013
      • クラウドソーシングにおけるワーカーの確信度を用いた高精度なラベル統合
        小山 聡; 馬場 雪乃; 櫻井 祐子; 鹿島 久嗣
        人工知能学会全国大会論文集, 2013
      • 「善い」マトリックスへの一歩?(<特集>編集委員今年の抱負2013)
        鹿島 久嗣
        人工知能学会誌, 01 Jan. 2013
      • Crowdsourcing and Machine Learning
        KASHIMA Hisashi; KAJINO Hiroshi
        人工知能学会誌 = Journal of Japanese Society for Artificial Intelligence, 01 Jul. 2012
      • Crowdsourcing and Machine Learning(Transfer of Knowledge)
        Kashima Hisashi; Kajino Hiroshi
        Journal of Japanese Society for Artificial Intelligence, 01 Jul. 2012
      • Matrix and Tensor Factorization with Aggregated Observations
        AIMOTO Yoshifumi; KASHIMA Hisashi
        電子情報通信学会技術研究報告. IBISML, 情報論的学習理論と機械学習, 05 Mar. 2012
      • A Kernel-based Approach for Matrix and Tensor Completion
        HAYASHI Kohei; TAKENOUCHI Takashi; TOMIOKA Ryota; KASHIMA Hisashi
        電子情報通信学会技術研究報告. IBISML, 情報論的学習理論と機械学習 = IEICE technical report. IBISML, Information-based induction sciences and machine learning, 02 Nov. 2011
      • A Convex Formulation of Learning from Crowds
        KAJINO Hiroshi; KASHIMA Hisashi
        電子情報通信学会技術研究報告. IBISML, 情報論的学習理論と機械学習 = IEICE technical report. IBISML, Information-based induction sciences and machine learning, 02 Nov. 2011
      • A Linear Time Subpath Kernel for Trees
        KIMURA Daisuke; KASHIMA Hisashi
        電子情報通信学会技術研究報告. IBISML, 情報論的学習理論と機械学習 = IEICE technical report. IBISML, Information-based induction sciences and machine learning, 02 Nov. 2011
      • A Kernel-based Approach for Matrix and Tensor Completion
        HAYASHI Kohei; TAKENOUCHI Takashi; TOMIOKA Ryota; KASHIMA Hisashi
        電子情報通信学会技術研究報告. IBISML, 情報論的学習理論と機械学習, 02 Nov. 2011
      • A Convex Formulation of Learning from Crowds
        KAJINO Hiroshi; KASHIMA Hisashi
        電子情報通信学会技術研究報告. IBISML, 情報論的学習理論と機械学習, 02 Nov. 2011
      • A Linear Time Subpath Kernel for Trees
        KIMURA Daisuke; KASHIMA Hisashi
        電子情報通信学会技術研究報告. IBISML, 情報論的学習理論と機械学習, 02 Nov. 2011
      • On the Convergence of Convex Tensor Estimation
        TOMIOKA Ryota; SUZUKI Taiji; HAYASHI Kohei; KASHIMA Hisashi
        IEICE technical report, 13 Jun. 2011
      • Tensor factorization using auxiliary information
        NARITA Atsuhiro; HAYASHI Kohei; TOMIOKA Ryota; KASHIMA Hisashi
        IEICE technical report, 21 Mar. 2011
      • Principal component analysis for multiple information sources
        SUWA Kyohei; TOMIOKA Ryota; YAIRI Takehisa; KASHIMA Hisashi
        IEICE technical report, 21 Mar. 2011
      • DK-2-5 高精度でスケーラブルな多項関係予測の実現を目指して(DK-2.JSTさきがけセッション:人と社会のための情報処理,ソサイエティ特別企画,ソサイエティ企画)
        鹿島 久嗣
        電子情報通信学会総合大会講演論文集, 28 Feb. 2011
      • DK-2-5 Toward Accurate and Scalable Multi-relational Prediction
        Kashima Hisashi
        Proceedings of the IEICE General Conference, 28 Feb. 2011
      • Statistical outlier detection using direct density ratio estimation.
        Shohei Hido; Yuta Tsuboi; Hisashi Kashima; Masashi Sugiyama; Takafumi Kanamori
        Knowl. Inf. Syst., 2011, Peer-reviewed
      • Return distribution estimation with dynamic programming
        MORIMURA Tetsuro; SUGIYAMA Masashi; KASHIMA Hisashi; HACHIYA Hirotaka; TANAKA Toshiyuki
        IEICE technical report, 28 Oct. 2010
      • Mining Graphs and Networks
        KASHIMA Hisashi
        The Journal of the Institute of Electronics, Information, and Communication Engineers, 01 Sep. 2010
      • Breakthrough Challenge for Practical Natural Language Processing(The Heisei 21 IPSJ Outstanding Paper Award)
        TSUBOI Yuta; MORI Shinsuke; KASHIMA Hisashi; ODA Hiroki; MATSUMOTO Yuji
        IPSJ Magazine, 15 Jul. 2010
      • Simultaneous inference of multiple biological networks
        鹿島 久嗣; 山西 芳裕; 加藤 毅
        IEICE technical report, 18 Jun. 2010
      • Simultaneous Inference of Multiple Biological Networks
        KASHIMA HISASHI; YAMANISHI YOSHIHIRO; KATO TSUYOSHI; SUGIYAMA MASASHI; TSUDA KOJI
        IPSJ SIG technical reports, 18 Jun. 2010
      • An SOCP Formulation for Multi-Task Learning
        加藤 毅; 鹿島 久嗣; 杉山 将; 浅井 潔
        情報処理学会研究報告, Apr. 2010
      • An SOCP Formulation for Multi-Task Learning
        Tsuyoshi Kato; Hisashi Kashima; Masashi Sugiyama; Kiyoshi Asai
        IPSJ SIG Notes, 25 Feb. 2010
      • Kernel Multivariate Analysis: New Trends in Nonlinear Data Analysis
        Kashima Hisashi
        Bulletin of the Japan Society for Industrial and Applied Mathematics, 25 Sep. 2009
      • Link Propagation: A Semi-supervised Approach to Link Prediction
        鹿島久嗣; 加藤毅; 山西芳裕; 杉山将; 津田宏治
        人工知能学会人工知能基本問題研究会資料, 06 Mar. 2009
      • Protein function prediction by integration of heterogeneous biological networks
        KATO TSUYOSHI; KASHIMA HISASHI; SUGIYAMA MASASHI
        IPSJ SIG technical reports, 11 Sep. 2008
      • A Spectrum Tree Kernel
        Kuboyama Tetsuji; Hirata Kouichi; Kashima Hisashi; Aoki-Kinoshita Kiyoko F; Yasuda Hiroshi
        IMT, 2007
      • The Gram Distribution Kernel: A Tree Kernel for Glycan Classification (テーマ:特集「ウェブデータの知的処理」および一般)
        Kuboyama Tetsuji; Hirata Koichi; Kashima Hisashi
        人工知能基本問題研究会, 08 Sep. 2006

      Books and Other Publications

      • ヒューマンコンピュテーションとクラウドソーシング (機械学習プロフェッショナルシリーズ)
        鹿島 久嗣; 小山 聡; 馬場 雪乃, Joint work
        講談社, 20 Apr. 2016, Not refereed
        Find Kyoto University's collection of books :
      • ヒューマンコンピュテーションとクラウドソーシング (機械学習プロフェッショナルシリーズ)
        鹿島久嗣; 小山聡; 馬場雪乃, Joint work
        講談社, 19 Apr. 2016, Not refereed
      • ヒューマンコンピュテーションとクラウドソーシング = Human computation and crowdsourcing
        鹿島, 久嗣; 小山, 聡; 馬場, 雪乃
        講談社, Apr. 2016
        Find Kyoto University's collection of books :
      • ビッグデータ・マネジメント―データサイエンティストのためのデータ利活用技術と事例
        嶋田茂; 首都大学東京; 伊藤大雄; 坂本 比呂志; 當仲寛哲; ユニバーサルシェルプログラミング研究; 鷲尾隆; 上田修功; 杉山将; 鹿島久嗣; 鈴木大慈; 河原大輔; 黒橋禎夫; 関根聡; 西尾信彦; 稲越宏弥; ほか
        エヌティーエス, 10 Mar. 2014, Not refereed
        Find Kyoto University's collection of books :
      • Google Hacks 第3版 ―プロが使うテクニック & ツール 100選
        山名 早人; 山名 早人; 石川 隼輔; 堀井 洋; 村上 明子; 鹿島 久嗣; 小柳 光生, Joint translation, Rael Dornfest; Paul Bausch; Tara Calishain
        オライリー・ジャパン, 24 Apr. 2007, Not refereed
        Find Kyoto University's collection of books :
      • Google Hacks : プロが使うテクニック&ツール100選
        Dornfest, Rael; Bausch, Paul; Calishain, Tara; 山名, 早人; 石川, 隼輔; 堀井, 洋; 村上, 明子; 鹿島, 久嗣; 小柳, 光生
        オライリー・ジャパン,オーム社 (発売), Apr. 2007
        Find Kyoto University's collection of books :
      • Google hacks : プロが使うテクニック&ツール100選
        Calishain, Tara; Dornfest, Rael; 石川, 隼輔; 堀井, 洋; 村上, 明子; 鹿島, 久嗣; 小柳, 光生; 山名, 早人, Joint work
        オライリー・ジャパン,オーム社 (発売), Aug. 2005, Not refereed
        Find Kyoto University's collection of books :

      Industrial Property Rights

      • 特開2017-126978, 特願2016-212574, 異常検知方法、異常検知装置及び異常検知システム
        氏家 良浩; 芳賀 智之; 前田 学; 松島 秀樹; 岸川 剛; 鶴見 淳一; 鹿島 久嗣; 鳥海 雪乃; 桑原 拓也
      • 特許第5306461号, 特願2011-520851, グラフの類似度計算システム、方法及びプログラム
        比戸 将平; 鹿島 久嗣
      • 特許第5225183号, 特開2010-250377, 特願2009-096248, リンク予測システム、方法及びプログラム
        ルディ・レイモンド・ハリー・プテラ; 鹿島 久嗣
      • 特許第5220582号, 特開2010-152568, 特願2008-328913, 新規顧客候補の評価作業を支援するための装置、方法及びプログラム
        柳▼澤 弘揮; 鹿島 久嗣; 田島 玲
      • 特許第5198981号, 特開2010-061323, 特願2008-225425, 作業評価値予測方法、プログラム及びシステム
        鹿島 久嗣; 比戸 将平; 田島 玲
      • 特許第5159368号, 特開2009-205615, 特願2008-049729, 変化分析システム、方法及びプログラム
        比戸 将平; 井手 剛; 鹿島 久嗣; 久保 晴信; 松澤 裕史
      • WO2011-001806, JP2010059795, グラフの類似度計算システム、方法及びプログラム
        比戸 将平; 鹿島 久嗣
      • 特開2010-250377, 特願2009-096248, リンク予測システム、方法及びプログラム
        ルディ・レイモンド・ハリー・プテラ; 鹿島 久嗣
      • 特開2010-152568, 特願2008-328913, 新規顧客候補の評価作業を支援するための装置、方法及びプログラム
        柳▼澤 弘揮; 鹿島 久嗣; 田島 玲
      • 特開2010-061323, 特願2008-225425, 作業評価値予測方法、プログラム及びシステム
        鹿島 久嗣; 比戸 将平; 田島 玲

      External funds: Kakenhi

      • Advancing Social Science through Market Design and its Practical Implementation
        Grant-in-Aid for Scientific Research (S)
        Broad Section A
        The University of Tokyo
        小島 武仁
        From 05 Jul. 2021, To 31 Mar. 2026, Granted
        マーケットデザイン;実用化;マッチング理論;オークション理論;東京大学マーケットデザインセンター
        https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-21H04979/
      • 複雑な関係データに基づく意思決定のための機械学習研究
        Grant-in-Aid for Scientific Research (B)
        Basic Section 61030:Intelligent informatics-related
        Kyoto University
        鹿島 久嗣
        From 01 Apr. 2020, To 31 Mar. 2024, Granted
        機械学習;人工知能;因果推論;グラフ;グラフ構造データ;意思決定;深層学習;グラフ深層学習
        https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-20H04244/
      • Creation of Incentive Design Science
        Grant-in-Aid for Scientific Research (A)
        Medium-sized Section 61:Human informatics and related fields
        Kyushu University
        横尾 真
        From 01 Apr. 2020, To 31 Mar. 2023, Granted
        ゲーム理論;人工知能;最適化;機械学習;実験経済学
        https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-20H00609/
      • The development of a fairness-aware data-transformation technique and the validation of its effectiveness through a cloudsoucing environment
        Grant-in-Aid for Scientific Research (B)
        Basic Section 61030:Intelligent informatics-related
        National Institute of Advanced Industrial Science and Technology
        Toshihiro Kamishima
        From 01 Apr. 2018, To 31 Mar. 2021, Project Closed
        公平性;クラウドソーシング;機械学習;データマイニング
        https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-18H03300/
      • Development of machine learning methods for materials informatics
        Grant-in-Aid for Scientific Research on Innovative Areas (Research in a proposed research area)
        Science and Engineering
        The University of Tokyo
        Koji Tsuda
        From 01 Apr. 2016, To 31 Mar. 2018, Project Closed
        マテリアルズインフォマティクス;機械学習
        https://kaken.nii.ac.jp/grant/KAKENHI-PLANNED-16H00736/
      • Machine Learning for Complex-Structured Data
        Grant-in-Aid for Scientific Research (A)
        Kyoto University
        Hisashi Kashima
        From 01 Apr. 2015, To 31 Mar. 2020, Project Closed
        人工知能;機械学習;データサイエンス;ヒューマンコンピュテーション;クラウドソーシング;集合知;機会学習;データマイニング
        https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-15H01704/
      • 機械学習に基づく材料探索技術の開発
        Grant-in-Aid for Scientific Research on Innovative Areas (Research in a proposed research area)
        Science and Engineering
        Kyoto University
        鹿島 久嗣
        From 01 Apr. 2014, To 31 Mar. 2016, Project Closed
        機械学習;材料科学
        https://kaken.nii.ac.jp/grant/KAKENHI-PUBLICLY-26106505/
      • Information Engineering Approach for Designing Supply Chain
        Grant-in-Aid for Scientific Research (B)
        The University of Tokyo
        Ichiro SAKATA
        From 01 Apr. 2012, To 31 Mar. 2015, Project Closed
        政策科学;サプライチェーン;技術経営;情報システム;機械学習
        https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-24310109/
      • Study on Information theoretic Learning Theory of Latent Dynamics
        Grant-in-Aid for Scientific Research (A)
        The University of Tokyo
        Kenji Yamanishi
        From 01 Apr. 2011, To 31 Mar. 2016, Project Closed
        情報論的学習理論;データマイニング;潜在的ダイナミクス;機械学習;ビッグデータ;変化検知;潜在変数モデル;潜在的ダイナミックス;モデル選択;異常検知;ネットワーク
        https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-23240019/
      • Predictive Machine Learning Methods for Graph-structured Data
        Grant-in-Aid for Young Scientists (A)
        Kyoto University;The University of Tokyo
        Hisashi KASHIMA
        From 01 Apr. 2010, To 31 Mar. 2015, Project Closed
        機械学習;人工知能;データマイニング;グラフ構造データ;ネットワークデータ;関係データ;予測;グラフ;ネットワーク;木
        https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-22680012/
      • 機械学習によるマルチスケール物理シミュレーションの高度化
        Grant-in-Aid for JSPS Fellows
        Basic Section 60100:Computational science-related
        Kyoto University
        From 28 Sep. 2022, To 31 Mar. 2025, Granted
        https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-22F22708/
      • 機械学習によるマルチスケール物理シミュレーションの高度化
        Grant-in-Aid for JSPS Fellows
        Basic Section 60100:Computational science-related
        Kyoto University
        鹿島 久嗣
        From 08 Mar. 2023, To 31 Mar. 2025, Granted
        https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-22KF0210/

      External funds: others

      • 人と AI の協働ヒューマンコンピュテーション基盤
        CREST
        From 01 Oct. 2021, To 31 Mar. 2027
        鹿島久嗣
      list
        Last Updated :2023/09/27

        Education

        Teaching subject(s)

        • From 01 Apr. 2023, To 31 Mar. 2024
          Foundations of Statistical Modeling
          9136, Spring, Faculty of Engineering, 2
        • From 01 Apr. 2023, To 31 Mar. 2024
          Introduction to Algorithms and Data Structures
          9115, Fall, Faculty of Engineering, 2
        • From 01 Apr. 2023, To 31 Mar. 2024
          Statistical Learning Theory
          X438, Spring, Graduate School of Engineering, 2
        • From 01 Apr. 2023, To 31 Mar. 2024
          Seminar of Data Science
          4714, Fall, Graduate School of Informatics, 2
        • From 01 Apr. 2023, To 31 Mar. 2024
          Statistical Learning Theory
          3178, Spring, Graduate School of Informatics, 2
        • From 01 Apr. 2023, To 31 Mar. 2024
          Introduction to Information Science
          3154, Spring, Graduate School of Informatics, 2
        • From 01 Apr. 2023, To 31 Mar. 2024
          Statistical Learning Theory
          M311, Spring, Institute for Liberal Arts and Sciences, 2
        • From 01 Apr. 2023, To 31 Mar. 2024
          Introduction to Information Science
          G202, Spring, Institute for Liberal Arts and Sciences, 2
        • From 01 Apr. 2023, To 31 Mar. 2024
          Statistics and Artificial Intelligence
          N817, Spring, Institute for Liberal Arts and Sciences, 2
        • From 01 Apr. 2022, To 31 Mar. 2023
          Seminar on Intelligence Science and Technology IV
          3196, Fall, Graduate School of Informatics, 2
        • From 01 Apr. 2022, To 31 Mar. 2023
          Statistics and Artificial Intelligence
          N817, Spring, Institute for Liberal Arts and Sciences, 2
        • From 01 Apr. 2022, To 31 Mar. 2023
          Seminar on Intelligence Science and Technology II
          3192, Spring, Graduate School of Informatics, 2
        • From 01 Apr. 2022, To 31 Mar. 2023
          Statistical Learning Theory
          3178, Spring, Graduate School of Informatics, 2
        • From 01 Apr. 2022, To 31 Mar. 2023
          Seminar on Intelligence Science and Technology I
          3191, Spring, Graduate School of Informatics, 2
        • From 01 Apr. 2022, To 31 Mar. 2023
          Statistics and Artificial Intelligence
          N817, Fall, Institute for Liberal Arts and Sciences, 2
        • From 01 Apr. 2022, To 31 Mar. 2023
          Seminar on Intelligence Science and Technology IV
          3197, Fall, Graduate School of Informatics, 2
        • From 01 Apr. 2022, To 31 Mar. 2023
          Seminar on Intelligence Science and Technology I
          3190, Spring, Graduate School of Informatics, 2
        • From 01 Apr. 2022, To 31 Mar. 2023
          Graduation Thesis 2
          9992, Fall, Faculty of Engineering, 3
        • From 01 Apr. 2022, To 31 Mar. 2023
          Seminar on Intelligence Science and Technology II
          3193, Spring, Graduate School of Informatics, 2
        • From 01 Apr. 2022, To 31 Mar. 2023
          Seminar on Intelligence Science and Technology III
          3195, Fall, Graduate School of Informatics, 2
        • From 01 Apr. 2022, To 31 Mar. 2023
          Graduation Thesis 1
          9991, Spring, Faculty of Engineering, 2
        • From 01 Apr. 2022, To 31 Mar. 2023
          Statistical Learning Theory
          X438, Spring, Graduate School of Engineering, 2
        • From 01 Apr. 2022, To 31 Mar. 2023
          Statistical Learning Theory
          M311, Spring, Institute for Liberal Arts and Sciences, 2
        • From 01 Apr. 2022, To 31 Mar. 2023
          Introduction to Algorithms and Data Structures
          9115, Fall, Faculty of Engineering, 2
        • From 01 Apr. 2022, To 31 Mar. 2023
          Graduation Thesis 2
          9992, Spring, Faculty of Engineering, 3
        • From 01 Apr. 2022, To 31 Mar. 2023
          Information and Business
          9108, Spring, Faculty of Engineering, 2
        • From 01 Apr. 2022, To 31 Mar. 2023
          Seminar on Intelligence Science and Technology III
          3194, Fall, Graduate School of Informatics, 2
        • From 01 Apr. 2022, To 31 Mar. 2023
          Introduction to Information Science
          G202, Spring, Institute for Liberal Arts and Sciences, 2
        • From 01 Apr. 2022, To 31 Mar. 2023
          Foundations of Statistical Modeling
          9136, Spring, Faculty of Engineering, 2
        • From 01 Apr. 2022, To 31 Mar. 2023
          Graduation Thesis 1
          9991, Fall, Faculty of Engineering, 2
        • From 01 Apr. 2022, To 31 Mar. 2023
          Introduction to Information Science
          3154, Spring, Graduate School of Informatics, 2
        • From Apr. 2015, To Mar. 2016
          Advanced Study in Intelligence Science and Technology I
          Year-long, 情報学研究科
        • From Apr. 2015, To Mar. 2016
          Advanced Study in Intelligence Science and Technology II
          Year-long, 情報学研究科
        • From Apr. 2015, To Mar. 2016
          Statistical Learning Theory
          Fall, 情報学研究科
        • From Apr. 2015, To Mar. 2016
          Humanistic Informatics (Special Lectures)
          Fall, 文学研究科
        • From Apr. 2015, To Mar. 2016
          Humanistic Informatics (Special Lectures)
          Fall, 文学部
        • From Apr. 2015, To Mar. 2016
          Introduction to Information Science
          Spring, 情報学研究科
        • From Apr. 2015, To Mar. 2016
          Information and Business
          Spring, 工学部
        • From Apr. 2015, To Mar. 2016
          Introduction to Algorithms and Data Structures
          Fall, 工学部
        • From Apr. 2015, To Mar. 2016
          Graduation Thesis 1
          Spring, 工学部
        • From Apr. 2015, To Mar. 2016
          Graduation Thesis 1
          Fall, 工学部
        • From Apr. 2015, To Mar. 2016
          Graduation Thesis 2
          Spring, 工学部
        • From Apr. 2015, To Mar. 2016
          Graduation Thesis 2
          Fall, 工学部
        • From Apr. 2015, To Mar. 2016
          Advanced Seminar on Intelligence Science and Technology
          Year-long, 情報学研究科
        • From Apr. 2015, To Mar. 2016
          Advanced Study in Intelligence Science and Technology II
          Year-long, 情報学研究科
        • From Apr. 2015, To Mar. 2016
          Advanced Study in Intelligence Science and Technology I
          Year-long, 情報学研究科
        • From Apr. 2015, To Mar. 2016
          Advanced Seminar on Foundation of Software Science
          Fall, 情報学研究科
        • From Apr. 2015, To Mar. 2016
          Introductory Statistics
          Spring, 全学共通科目
        • From Apr. 2015, To Mar. 2016
          Statistical Learning Theory
          Fall, 工学研究科
        • From Apr. 2016, To Mar. 2017
          Advanced Study in Intelligence Science and Technology I
          Year-long, 情報学研究科
        • From Apr. 2016, To Mar. 2017
          Advanced Study in Intelligence Science and Technology II
          Year-long, 情報学研究科
        • From Apr. 2016, To Mar. 2017
          Statistical Learning Theory
          Spring, 情報学研究科
        • From Apr. 2016, To Mar. 2017
          Humanistic Informatics (Special Lectures)
          Fall, 文学研究科
        • From Apr. 2016, To Mar. 2017
          Humanistic Informatics (Special Lectures)
          Fall, 文学部
        • From Apr. 2016, To Mar. 2017
          Introduction to Information Science
          Spring, 情報学研究科
        • From Apr. 2016, To Mar. 2017
          Introduction to Algorithms and Data Structures
          Fall, 工学部
        • From Apr. 2016, To Mar. 2017
          Advanced Seminar on Intelligence Science and Technology
          Year-long, 情報学研究科
        • From Apr. 2016, To Mar. 2017
          Advanced Study in Intelligence Science and Technology II
          Year-long, 情報学研究科
        • From Apr. 2016, To Mar. 2017
          Advanced Study in Intelligence Science and Technology I
          Year-long, 情報学研究科
        • From Apr. 2016, To Mar. 2017
          Advanced Seminar on Foundation of Software Science
          Fall, 情報学研究科
        • From Apr. 2016, To Mar. 2017
          Introductory Statistics
          Fall, 全学共通科目
        • From Apr. 2016, To Mar. 2017
          Statistical Learning Theory
          Spring, 工学研究科
        • From Apr. 2017, To Mar. 2018
          Advanced Study in Intelligence Science and Technology I
          Year-long, 情報学研究科
        • From Apr. 2017, To Mar. 2018
          Advanced Study in Intelligence Science and Technology II
          Year-long, 情報学研究科
        • From Apr. 2017, To Mar. 2018
          Statistical Learning Theory
          Spring, 情報学研究科
        • From Apr. 2017, To Mar. 2018
          Humanistic Informatics (Special Lectures)
          Fall, 文学研究科
        • From Apr. 2017, To Mar. 2018
          Humanistic Informatics (Special Lectures)
          Fall, 文学部
        • From Apr. 2017, To Mar. 2018
          Introduction to Information Science
          Spring, 情報学研究科
        • From Apr. 2017, To Mar. 2018
          Introduction to Algorithms and Data Structures
          Fall, 工学部
        • From Apr. 2017, To Mar. 2018
          Advanced Seminar on Intelligence Science and Technology
          Year-long, 情報学研究科
        • From Apr. 2017, To Mar. 2018
          Advanced Study in Intelligence Science and Technology II
          Year-long, 情報学研究科
        • From Apr. 2017, To Mar. 2018
          Advanced Study in Intelligence Science and Technology I
          Year-long, 情報学研究科
        • From Apr. 2017, To Mar. 2018
          Advanced Seminar on Foundation of Software Science
          Fall, 情報学研究科
        • From Apr. 2017, To Mar. 2018
          Introductory Statistics
          Fall, 全学共通科目
        • From Apr. 2017, To Mar. 2018
          Foundations of Statistical Modeling
          Spring, 工学部
        • From Apr. 2017, To Mar. 2018
          Statistical Learning Theory
          Spring, 工学研究科
        • From Apr. 2018, To Mar. 2019
          Statistical Learning Theory
          Spring, 全学共通科目
        • From Apr. 2018, To Mar. 2019
          Statistical Learning Theory
          Spring, 情報学研究科
        • From Apr. 2018, To Mar. 2019
          Introduction to Information Science
          Spring, 全学共通科目
        • From Apr. 2018, To Mar. 2019
          Introduction to Information Science
          Spring, 情報学研究科
        • From Apr. 2018, To Mar. 2019
          Media and Culture Studies (Special Lectures)
          Fall, 文学研究科
        • From Apr. 2018, To Mar. 2019
          Media and Culture Studies (Special Lectures)
          Fall, 文学部
        • From Apr. 2018, To Mar. 2019
          Introduction to Algorithms and Data Structures
          Fall, 工学部
        • From Apr. 2018, To Mar. 2019
          Foundations of Statistical Modeling
          Spring, 工学部
        • From Apr. 2018, To Mar. 2019
          Statistical Learning Theory
          Spring, 工学研究科
        • From Apr. 2018, To Mar. 2019
          Second Course in Statistics
          Fall, 全学共通科目
        • From Apr. 2019, To Mar. 2020
          Statistical Learning Theory
          Spring, 全学共通科目
        • From Apr. 2019, To Mar. 2020
          Introduction to Information Science
          Spring, 全学共通科目
        • From Apr. 2019, To Mar. 2020
          Introduction to Information Science
          Spring, 情報学研究科
        • From Apr. 2019, To Mar. 2020
          Introduction to Algorithms and Data Structures
          Fall, 工学部
        • From Apr. 2019, To Mar. 2020
          Foundations of Statistical Modeling
          Spring, 工学部
        • From Apr. 2019, To Mar. 2020
          Statistical Learning Theory
          Spring, 工学研究科
        • From Apr. 2019, To Mar. 2020
          Statistical Learning Theory
          Spring, 情報学研究科
        • From Apr. 2019, To Mar. 2020
          Second Course in Statistics
          Fall, 全学共通科目
        • From Apr. 2020, To Mar. 2021
          Statistical Learning Theory
          Spring, 全学共通科目
        • From Apr. 2020, To Mar. 2021
          Introduction to Information Science
          Spring, 全学共通科目
        • From Apr. 2020, To Mar. 2021
          Introduction to Information Science
          Spring, 情報学研究科
        • From Apr. 2020, To Mar. 2021
          Introduction to Algorithms and Data Structures
          Fall, 工学部
        • From Apr. 2020, To Mar. 2021
          Statistics and Artificial Intelligence
          Spring, 全学共通科目
        • From Apr. 2020, To Mar. 2021
          Statistics and Artificial Intelligence
          Fall, 全学共通科目
        • From Apr. 2020, To Mar. 2021
          Foundations of Statistical Modeling
          Spring, 工学部
        • From Apr. 2020, To Mar. 2021
          Statistical Learning Theory
          Spring, 工学研究科
        • From Apr. 2020, To Mar. 2021
          Statistical Learning Theory
          Spring, 情報学研究科
        • From Apr. 2021, To Mar. 2022
          Seminar on Intelligence Science and Technology III
          Fall, 情報学研究科
        • From Apr. 2021, To Mar. 2022
          Seminar on Intelligence Science and Technology II
          Spring, 情報学研究科
        • From Apr. 2021, To Mar. 2022
          Seminar on Intelligence Science and Technology I
          Spring, 情報学研究科
        • From Apr. 2021, To Mar. 2022
          Seminar on Intelligence Science and Technology IV
          Fall, 情報学研究科
        • From Apr. 2021, To Mar. 2022
          Statistical Learning Theory
          Spring, 全学共通科目
        • From Apr. 2021, To Mar. 2022
          Introduction to Information Science
          Spring, 全学共通科目
        • From Apr. 2021, To Mar. 2022
          Introduction to Information Science
          Spring, 情報学研究科
        • From Apr. 2021, To Mar. 2022
          Introduction to Algorithms and Data Structures
          Fall, 工学部
        • From Apr. 2021, To Mar. 2022
          Seminar on Intelligence Science and Technology III
          Fall, 情報学研究科
        • From Apr. 2021, To Mar. 2022
          Seminar on Intelligence Science and Technology II
          Spring, 情報学研究科
        • From Apr. 2021, To Mar. 2022
          Seminar on Intelligence Science and Technology I
          Spring, 情報学研究科
        • From Apr. 2021, To Mar. 2022
          Seminar on Intelligence Science and Technology IV
          Fall, 情報学研究科
        • From Apr. 2021, To Mar. 2022
          Statistics and Artificial Intelligence
          Spring, 全学共通科目
        • From Apr. 2021, To Mar. 2022
          Statistics and Artificial Intelligence
          Fall, 全学共通科目
        • From Apr. 2021, To Mar. 2022
          Foundations of Statistical Modeling
          Spring, 工学部
        • From Apr. 2021, To Mar. 2022
          Statistical Learning Theory
          Spring, 工学研究科
        • From Apr. 2021, To Mar. 2022
          Statistical Learning Theory
          Spring, 情報学研究科

        Participation in PhD Defense

        • Improving Variational Autoencoders on Robustness, Regularization, and Task-Invariance
          Hiroshi Takahashi, Graduate School of Informatics, Chief Examiner
          23 Mar. 2023
        • Treatment Effect Estimation from Small Observational Data
          HARADA SHONOSUKE, Graduate School of Informatics, Chief Examiner
          23 Mar. 2023
        • Causal Inference for Scientific Discoveries and Fairness-Aware Machine Learning
          Yoichi Chikahara, Graduate School of Informatics, Chief Examiner
          26 Sep. 2022
        • Spatio-temporal Event Prediction via Deep Point Processes
          OKAWA MAYA, Graduate School of Informatics, Chief Examiner
          23 Mar. 2022
        • Studies on Fundamental Problems in Event-Level Language Analysis
          KIYOMARU HIROKAZU, Graduate School of Informatics, Sub-chief Examiner
          23 Mar. 2022
        • Predicting with Structured Data: Graphs, Ranks, and Time Series
          Jiuding Duan, Graduate School of Informatics, Chief Examiner
          26 Jul. 2021
        • Goal-oriented Modeling for Data-driven Decision Making
          Akira Tanimoto, Graduate School of Informatics, Chief Examiner
          24 Sep. 2021
        • Design of Computational Models for Analyzing Graph-Structured Biological Data
          WANG Feiqi, Graduate School of Informatics, Sub-chief Examiner
          23 Mar. 2022
        • A Unified Generative and Discriminative Approach to Automatic Chord Estimation for Music Audio Signals
          Yiming Wu, Graduate School of Informatics, Sub-chief Examiner
          24 Sep. 2021
        • Extracting Rules from Trained Machine Learning Models with Applications in Bioinformatics
          LIU PENGYU, Graduate School of Informatics, Sub-chief Examiner
          24 May 2021
        list
          Last Updated :2023/09/27

          Administration

          School management (title, position)

          • From 01 Apr. 2023, To 31 Mar. 2024
            国際高等教育院 企画評価専門委員会 データ科学部会 委員
          • From 01 Apr. 2023, To 31 Mar. 2024
            大学院教育支援機構 大学院共通・横断教育企画評価専門委員会 データ科学部会 委員
          • From 01 Apr. 2022, To 31 Mar. 2023
            国際高等教育院 企画評価専門委員会 データ科学部会 委員
          • From 01 Jun. 2016, To 01 Jul. 2018
            学生生活委員会 委員
          • From 01 Jun. 2016, To 01 Jul. 2018
            学生生活委員会第三小委員会 委員
          • From 01 May 2017, To 31 Mar. 2019
            国際高等教育院 企画評価専門委員会 データ科学部会 委員
          • From 01 May 2016, To 30 Apr. 2017
            国際高等教育院 企画評価専門委員会 統計教育特別部会 委員
          • From 01 Jun. 2015, To 30 Apr. 2016
            国際高等教育院 企画評価専門委員会 統計特別部会 委員
          • From 01 May 2017, To 31 Mar. 2019
            国際高等教育院 基盤企画評価専門委員会 データ科学部会 委員
          • From 01 Apr. 2019, To 31 Mar. 2020
            国際高等教育院 基盤企画評価専門委員会 データ科学部会 委員
          • From 01 Apr. 2019, To 31 Mar. 2020
            国際高等教育院 企画評価専門委員会 データ科学部会 委員
          • From 01 Apr. 2020, To 31 Mar. 2021
            国際高等教育院 基盤企画評価専門委員会 データ科学部会 委員
          • From 01 Apr. 2020, To 31 Mar. 2021
            国際高等教育院 企画評価専門委員会 データ科学部会 委員
          • From 01 Apr. 2021, To 31 Mar. 2022
            国際高等教育院 基盤企画評価専門委員会 データ科学部会 委員
          • From 01 Apr. 2021, To 31 Mar. 2022
            国際高等教育院 企画評価専門委員会 データ科学部会 委員

          Faculty management (title, position)

          • From 01 Apr. 2023, To 31 Mar. 2025
            工学部新工学教育実施専門委員会　委員
          • From 01 Apr. 2023, To 31 Mar. 2024
            教務委員会委員長
          • From 01 Apr. 2022, To 31 Mar. 2023
            情報学科長
          • From 01 Apr. 2022, To 31 Mar. 2023
            財務委員会委員
          • From 01 Apr. 2014, To 31 Mar. 2015
            評価・広報委員会委員
          • From 01 Apr. 2015, To 31 Mar. 2017
            連携推進ＷＧ委員
          • From 01 Apr. 2015, To 31 Mar. 2017
            企画委員会副委員長
          • From 01 Apr. 2016, To 31 Mar. 2018
            工学研究科・工学部広報委員会　委員
          • From 01 Apr. 2017, To 31 Mar. 2018
            専攻長会議
          • From 01 Apr. 2017, To 31 Mar. 2018
            制規委員会
          • From 01 Apr. 2017, To 31 Mar. 2018
            情報セキュリティ委員会委員
          • From 01 Apr. 2018, To 31 Mar. 2019
            情報セキュリティ委員会委員
          • From 01 Apr. 2018, To 31 Mar. 2019
            専攻長
          • From 01 Apr. 2018, To 31 Mar. 2019
            制規委員会委員
          • From 01 Apr. 2018, To 31 Mar. 2019
            連携推進WG
          • From 01 Apr. 2019, To 31 Mar. 2020
            基盤整備委員会委員
          • From 01 Apr. 2019, To 31 Mar. 2020
            計算機小委員会委員長
          • From 01 Apr. 2020, To 31 Mar. 2021
            基盤整備委員会委員長
          • From 01 Apr. 2020, To 31 Mar. 2021
            工学部教育制度委員会委員
          • From 01 Apr. 2021, To 31 Mar. 2022
            財務委員会委員長
          • From 01 Apr. 2021, To 31 Mar. 2022
            工学研究科・工学部広報委員会委員

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