Basic Information

Faculty

• 工学部

Academic Degree

• 修士（工学）(早稲田大学)
• 博士（情報学）(京都大学)

Research History

• From Feb. 2020, To Present

  Kyoto University, Graduate School of Informatics Department of Intelligence Science and Technology, 助教
• From Apr. 2011, To Jan. 2020

  NTT, Communication Science Labs., Researcher

ID,URL

• J-Global ID

  201801000653333518

• External link

  https://www.ml.ist.i.kyoto-u.ac.jp/koh.takeuchi/

researchmap URL

• https://researchmap.jp/koh.t

Research

Research Interests

• Data Mining
• Machine Learning

Research Areas

• Informatics, Intelligent informatics

Papers

• Multiview Representation Learning from Crowdsourced Triplet Comparisons.

  Xiaotian Lu; Jiyi Li; Koh Takeuchi; Hisashi Kashima

  WWW, 2023

  
• District Characteristics Analysis with Regional Garbage Amount Estimation Using Vehicle- Mounted Motion Sensors.

  Yasue Kishino; Yoshinari Shirai; Koh Takeuchi; Shin Mizutani; Takayuki Suyama; Futoshi Naya; Naonori Ueda

  ISC2, 2022

  
• Mitigating Observation Biases in Crowdsourced Label Aggregation.

  Ryosuke Ueda; Koh Takeuchi; Hisashi Kashima

  ICPR, 2022

  
• Estimating counterfactual treatment outcomes over time in multi-vehicle simulation.

  Keisuke Fujii 0001; Koh Takeuchi; Atsushi Kuribayashi; Naoya Takeishi; Yoshinobu Kawahara; Kazuya Takeda

  SIGSPATIAL/GIS, 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

  
• Predicting Anesthetic Infusion Events Using Machine Learning

  Naoki Miyaguchi; Koh Takeuchi; Hisashi Kashima; Mizuki Morita; Hiroshi Morimatsu

  Scientific Reports, 19 Nov. 2021, Peer-reviewed

  
• Discriminant Dynamic Mode Decomposition for Labeled Spatiotemporal Data Collections.

  Naoya Takeishi; Keisuke Fujii 0001; Koh Takeuchi; Yoshinobu Kawahara

  SIAM J. Appl. Dyn. Syst., 2022

  
• Time Series Link Prediction Using NMF.

  Faith W. Mutinda; Atsuhiro Nakashima; Koh Takeuchi; Yuya Sasaki; Makoto Onizuka

  IEEE International Conference on Big Data and Smart Computing, BigComp 2019, Kyoto, Japan, February 27 - March 2, 2019, 2019, Peer-reviewed

  
• Non-linear Attributed Graph Clustering by Symmetric NMF with PU Learning.

  Seiji Maekawa; Koh Takeuchi; Makoto Onizuka

  CoRR, 2018, Peer-reviewed

  
• Fréchet Kernel for Trajectory Data Analysis.

  Koh Takeuchi; Masaaki Imaizumi; Shunsuke Kanda; Yasuo Tabei; Keisuke Fujii; Ken Yoda; Masakazu Ishihata; Takuya Maekawa

  ACM SIGSPATIAL, 2021, Peer-reviewed, Lead author

  
• 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

  IEEE ITSC, 2021, Peer-reviewed

  
• Crowdsourcing Evaluation of Saliency-based XAI Methods.

  Xiaotian Lu; Arseny Tolmachev; Tatsuya Yamamoto; Koh Takeuchi; Seiji Okajima; Tomoyoshi Takebayashi; Koji Maruhashi; Hisashi Kashima

  ECMLPKDD, 2021, Peer-reviewed

  
• Inter-domain Multi-relational Link Prediction.

  Luu Huu Phuc; Koh Takeuchi; Seiji Okajima; Arseny Tolmachev; Tomoyoshi Takebayashi; Koji Maruhashi; Hisashi Kashima

  ECMLPKDD, 2021, Peer-reviewed

  
• Grab the Reins of Crowds: Estimating the Effects of Crowd Movement Guidance Using Causal Inference.

  Koh Takeuchi; Ryo Nishida; Hisashi Kashima; Masaki Onishi

  AAMAS, 2021, Peer-reviewed, Lead author

  
• Fast Deterministic CUR Matrix Decomposition with Accuracy Assurance.

  Yasutoshi Ida; Sekitoshi Kanai; Yasuhiro Fujiwara; Tomoharu Iwata; Koh Takeuchi; Hisashi Kashima

  ICML, 2020, Peer-reviewed

  
• Succinct Trit-array Trie for Scalable Trajectory Similarity Search.

  Shunsuke Kanda; Koh Takeuchi; Keisuke Fujii; Yasuo Tabei

  ACM SIGSPATIAL, 2020, Peer-reviewed

  
• Simultaneous Link Prediction on Unaligned Networks Using Graph Embedding and Optimal Transport.

  Luu Huu Phuc; Koh Takeuchi; Makoto Yamada; Hisashi Kashima

  IEEE DSAA, 2020, Peer-reviewed

  
• Proximity Preserving Nonnegative Matrix Factorization.

  Yuya Ogawa; Koh Takeuchi; Yuya Sasaki 0001; Makoto Onizuka

  J. Inf. Process., 2020, Peer-reviewed

  
• New Attributed Graph Clustering by Bridging Attribute and Topology Spaces.

  Seiji Maekawa; Koh Takeuchi; Makoto Onizuka

  J. Inf. Process., 2020, Peer-reviewed

  
• 隣接性と構造類似性を考慮したグラフクラスタリング

  小川 裕也; 前川 政司; 竹内 孝; 佐々木 勇和; 鬼塚 真

  Mar. 2019

  
• Variational Inference of Penalized Regression with Submodular Functions.

  Koh Takeuchi; Yuichi Yoshida; Yoshinobu Kawahara

  UAI, 2019, Peer-reviewed, Lead author

  
• Time Series Link Prediction Using NMF.

  Faith W. Mutinda; Atsuhiro Nakashima; Koh Takeuchi; Yuya Sasaki 0001; Makoto Onizuka

  J. Inf. Process., 2019, Peer-reviewed

  
• Accelerating Urban Science by Crowdsensing with Civil Officers.

  Takuro Yonezawa; Koh Takeuchi; Tomotaka Ito; Mina Sakamura; Yasue Kishino; Futoshi Naya; Naonori Ueda; Jin Nakazawa

  Ubicomp, 2018, Peer-reviewed

  
• Regional Garbage Amount Estimation and Analysis Using Car-Mounted Motion Sensors.

  Yasue Kishino; Yoshinari Shirai; Koh Takeuchi; Takayuki Suyama; Futoshi Naya; Naonori Ueda

  Ubicomp, 2018, Peer-reviewed

  
• Few-shot learning of neural networks from scratch by pseudo example optimization.

  Akisato Kimura; Zoubin Ghahramani; Koh Takeuchi; Tomoharu Iwata; Naonori Ueda

  BMVC, 2018, Peer-reviewed

  
• Mobile Network Failure Event Detection and Forecasting With Multiple User Activity Data Sets.

  Motoyuki Oki; Koh Takeuchi; Yukio Uematsu

  IAAI, 2018, Peer-reviewed

  
• Scaling Locally Linear Embedding.

  Yasuhiro Fujiwara; Naoki Marumo; Mathieu Blondel; Koh Takeuchi; Hideaki Kim; Tomoharu Iwata; Naonori Ueda

  Proceedings of the 2017 ACM International Conference on Management of Data, 2017

  
• Structurally Regularized Non-negative Tensor Factorization for Spatio-Temporal Pattern Discoveries.

  Koh Takeuchi; Yoshinobu Kawahara; Tomoharu Iwata

  Machine Learning and Knowledge Discovery in Databases - European Conference, 2017

  
• SVD-Based Screening for the Graphical Lasso.

  Yasuhiro Fujiwara; Naoki Marumo; Mathieu Blondel; Koh Takeuchi; Hideaki Kim; Tomoharu Iwata; Naonori Ueda

  Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence(IJCAI), 2017

  
• Autoregressive Tensor Factorization for Spatio-Temporal Predictions.

  Koh Takeuchi; Hisashi Kashima; Naonori Ueda

  2017 IEEE International Conference on Data Mining(ICDM), 2017

  
• Datafying city: Detecting and accumulating spatio-temporal events by vehicle-mounted sensors.

  Yasue Kishino; Koh Takeuchi; Yoshinari Shirai; Futoshi Naya; Naonori Ueda

  2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017

  
• Localized Lasso for High-Dimensional Regression.

  Makoto Yamada; Koh Takeuchi; Tomoharu Iwata; John Shawe-Taylor; Samuel Kaski

  Proceedings of the 20th International Conference on Artificial Intelligence and Statistics(AISTATS), 2017

  
• Sparse Network Lasso for Local High-dimensional Regression.

  Makoto Yamada; Koh Takeuchi; Tomoharu Iwata; John Shawe-Taylor; Samuel Kaski

  CoRR, 2016

  
• Higher Order Fused Regularization for Supervised Learning with Grouped Parameters.

  Koh Takeuchi; Yoshinobu Kawahara; Tomoharu Iwata

  Machine Learning and Knowledge Discovery in Databases - European Conference, 2015

  
• Cross-domain recommendation without shared users or items by sharing latent vector distributions.

  Tomoharu Iwata; Koh Takeuchi

  Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics(AISTATS), 2015

  
• Non-Negative Multiple Matrix Factorization.

  Koh Takeuchi; Katsuhiko Ishiguro; Akisato Kimura; Hiroshi Sawada

  IJCAI 2013(IJCAI), 2013

  
• Non-negative Multiple Tensor Factorization.

  Koh Takeuchi; Ryota Tomioka; Katsuhiko Ishiguro; Akisato Kimura; Hiroshi Sawada

  2013 IEEE 13th International Conference on Data Mining(ICDM), 2013

  
• Towards Automatic Image Understanding and Mining via Social Curation.

  Katsuhiko Ishiguro; Akisato Kimura; Koh Takeuchi

  12th IEEE International Conference on Data Mining(ICDM), 2012

  

Misc.

• Preliminary Investigation of Unsupervised Segmentation for Animal Locomotion Data using Deep Learning

  TSUJIMOTO Hiroki; TAKEUCHI Koh; KISHINO Yasue; SUZUKI Hirokazu; YODA Ken; KIMURA Koutarou D.; MAEKAWA Takuya; HARA Takahiro

  Proceedings of the Annual Conference of JSAI, Jun. 2020

  
• 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

  
• Model Ensemble for Failure Event Detection using Multiple User Activity Data on the Web

  大木 基至; 竹内 孝; 植松 幸生

  電子情報通信学会技術研究報告 = IEICE technical report : 信学技報, 18 Sep. 2017

  
• 特徴的な構造を抽出するデータマイニング技術 (特集 情報と人間を結ぶコミュニケーション科学)

  石黒 勝彦; 竹内 孝

  NTT技術ジャーナル, Sep. 2012

  
• Structured regularizer for spatio-temporal matrix completion

  竹内 孝; 河原 吉伸; 岩田 具治

  人工知能基本問題研究会, 27 Mar. 2016

  
• Analyzing Picture Book Data with Non-negative Multiple Matrix Factorization : Extended Abstract

  竹内 孝; 石黒 勝彦; 小林 哲生

  人工知能学会全国大会論文集, 2014

  
• Multiple Matrix Factorization under the Non-negative Constraints and its Applications for Social Media Analysis

  竹内 孝; 石黒 勝彦; 木村 昭悟; 澤田 宏

  情報処理学会論文誌数理モデル化と応用（TOM）, 28 Mar. 2014

  
• Multiple Matrix Factorization under the Non-negative Constraints

  Koh Takeuchi; Katsuhiko Ishiguro; Akisato Kimura; Hiroshi Sawada

  IPSJ SIG Notes, 16 May 2013

  
• sNMF : Stacked Non-negative Matrix Factorization : Its Application For Social Media Analysis

  TAKEUCHI Koh; ISHIGURO Katsuhiko; KIMURA Akisato; SAWADA Hiroshi

  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, 31 Oct. 2012

  

External funds: Kakenhi

• Development of machine learning algorithms based on discrete convex analysis

  Grant-in-Aid for Scientific Research (B)

  Osaka University

  Yoshinobu Kawahara

  From 01 Apr. 2014, To 31 Mar. 2018, Project Closed

  機械学習;組合せ最適化;最適化

  https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-26280086/
• 自律的に計測・介入を行うχログボットのアルゴリズム開発

  Grant-in-Aid for Transformative Research Areas (A)

  Transformative Research Areas, Section (IV)

  Osaka University

  前川 卓也

  From 10 Sep. 2021, To 31 Mar. 2026, Granted

  階層的生物ナビ学;動物行動学;機械学習;ユビキタスコンピューティング

  https://kaken.nii.ac.jp/grant/KAKENHI-PLANNED-21H05299/

Education

Teaching subject(s)

• From 01 Apr. 2023, To 31 Mar. 2024

  Mathematics in Practice for Computer Science

  9131, Spring, Faculty of Engineering, 2
• From 01 Apr. 2023, To 31 Mar. 2024

  Computer Science Laboratory and Exercise 1

  9138, Spring, Faculty of Engineering, 2
• From 01 Apr. 2023, To 31 Mar. 2024

  Statistical Learning Theory

  M311, Spring, Institute for Liberal Arts and Sciences, 2
• From 01 Apr. 2022, To 31 Mar. 2023

  Computer Science Laboratory and Exercise 2

  9022, Fall, Faculty of Engineering, 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

  Computer Science Laboratory and Exercise 1

  9138, Spring, Faculty of Engineering, 2
• From Apr. 2021, To Mar. 2022

  Computer Science Laboratory and Exercise 1

  Spring, 工学部
• From Apr. 2021, To Mar. 2022

  Computer Science Laboratory and Exercise 1

  Spring, 工学部

Administration

Faculty management (title, position)

• From 01 Apr. 2021, To 31 Mar. 2022

  広報WG委員

Academic, Social Contribution

Committee Memberships

• From 2023

  プログラム委員, 第26回情報論的学習理論ワークショップ (IBIS2023)
• From 2023

  Local Chair, The Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD)
• From 2021, To 2023

  Program Committee, The Annual Conference of the Japanese Society for Artificial Intelligence
• From 2019

  Program Committee, The 22nd information-Based Induction Sciences Workshop
• From 2016

  Program Comittie, The 19th information-Based Induction Sciences Workshop