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 Oct. 2023, To Present

  Kyoto University, Graduate School of Informatics Department of Intelligence Science and Technology, Senior Lecturer
• From Feb. 2020, To Sep. 2023

  Kyoto University, Graduate School of Informatics Department of Intelligence Science and Technology, Assistant Professor
• 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

• Cognitive Biases in Large Language Models: A Survey and Mitigation Experiments.

  Yasuaki Sumita; Koh Takeuchi 0001; Hisashi Kashima

  SAC, 2025

  
• Travel Demand Prediction with Application to Commuter Demand Estimation on Urban Railways.

  Yohei Kodama; Yuki Akeyama; Yusuke Miyazaki 0005; Koh Takeuchi 0001

  Companion Proceedings of the ACM on Web Conference 2024, 2024

  
• Recovering Population Dynamics from a Single Point Cloud Snapshot.

  Yuki Wakai; Koh Takeuchi 0001; Hisashi Kashima

  Advances in Knowledge Discovery and Data Mining - 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, 2024

  
• AHP-Powered LLM Reasoning for Multi-Criteria Evaluation of Open-Ended Responses.

  Xiaotian Lu; Jiyi Li; Koh Takeuchi 0001; Hisashi Kashima

  Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

  
• Evaluating Saliency Explanations in NLP by Crowdsourcing.

  Xiaotian Lu; Jiyi Li; Zhen Wan; Xiaofeng Lin 0001; Koh Takeuchi 0001; Hisashi Kashima

  Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation(LREC/COLING), 2024

  
• Estimating counterfactual treatment outcomes over time in complex multi-agent scenarios.

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

  CoRR, 2022

  
• Scalable individual treatment effect estimator for large graphs.

  Xiaofeng Lin 0001; Han Bao 0002; Yan Cui 0008; Koh Takeuchi 0001; Hisashi Kashima

  Mach. Learn., Jan. 2025

  Access this paper :

  
• Extracting essential structure from data

  Katsuhiko Ishiguro; Koh Takeuchi

  NTT Technical Review, Nov. 2012

  
• Imitation networks: Few-shot learning of neural networks from scratch.

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

  CoRR, 2018

  
• Estimating Treatment Effects Under Heterogeneous Interference.

  Xiaofeng Lin; Guoxi Zhang; Xiaotian Lu; Han Bao 0002; Koh Takeuchi; Hisashi Kashima

  CoRR, 2023

  
• Estimating Counterfactual Treatment Outcomes Over Time in Complex Multiagent Scenarios

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

  IEEE Transactions on Neural Networks and Learning Systems, 2024

  
• Bleeding alert map (BAM): The identification method of the bleeding source in real organs using datasets made on mimicking organs.

  Maina Sogabe; Kaoru Ishikawa; Toshihiro Takamatsu; Koh Takeuchi; Takahiro Kanno; Koji Fujimoto; Tetsuro Miyazaki; Toshihiro Kawase; Toshihiko Sato; Kenji Kawashima

  Array, Sep. 2023

  
• Estimating Treatment Effects Under Heterogeneous Interference.

  Xiaofeng Lin; Guoxi Zhang; Xiaotian Lu; Han Bao 0002; Koh Takeuchi; Hisashi Kashima

  ECML/PKDD (1), 2023

  
• QTNet: Theory-based Queue Length Prediction for Urban Traffic.

  Ryu Shirakami; Toshiya Kitahara; Koh Takeuchi; Hisashi Kashima

  KDD, 2023

  
• Causal Effect Estimation on Hierarchical Spatial Graph Data.

  Koh Takeuchi; Ryo Nishida; Hisashi Kashima; Masaki Onishi

  KDD, 2023

  
• Mitigating Voter Attribute Bias for Fair Opinion Aggregation.

  Ryosuke Ueda; Koh Takeuchi; Hisashi Kashima

  AIES, 2023

  
• 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.

• Deep few-shot learning with pseudo example optimization

  木村昭悟; 木村昭悟; GHAHRAMANI Zoubin; 竹内孝; 岩田具治; 上田修功

  人工知能学会全国大会論文集(CD-ROM), 2018

  
• 機械学習を用いたグラフ構造データの解析と応用

  竹内 孝

  人工知能, 01 Mar. 2023

  
• 会議報告：The 20th International Conference on Autonomous Agents and Multiagent Systems（ AAMAS-2021）

  竹内 孝

  人工知能, 01 Sep. 2021

  
• 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

  

Media Coverage

• 住友電工、AIで渋滞予測 京大と開発、物流24年問題に対策

  日本経済新聞, 7面、電子版, 27 Dec. 2023, Paper

  
• 交通渋滞を正確に予測するAIを開発警視庁データで学習、1時間先の誤差40メートル以下

  JSTnews, 11月号, NEWS&TOPICS, 紙面・電子版, Nov. 2023, Paper

  
• 1時間先の渋滞を正確に予測できる！

  子供の科学, 2023年11月号, 紙面, Nov. 2023, Paper

  
• AI使い信号制御、都内の渋滞対策 警視庁が全国初導入

  日本経済新聞, 紙面1面・電子版, 19 Oct. 2023, Paper

  
• 交通渋滞の長さを精度良く予測、京大などがAI開発 警視庁のビッグデータで学習

  サイエンスポータル, Yahoo!ニュース、 マイナビニュース、 Lab BRAINS, 電子版, 05 Oct. 2023, Internet

  
• 京都大学和住友电工系统开发出可准确预测交通拥堵长度的AI，实现“误差小于40米”的高精度预测

  客观日本, 電子版, 02 Oct. 2023, Internet

  
• 渋滞を正確に予測するAI

  現代化学, 2023年10月号, Oct. 2023, Paper

  
• Kyoto University and Sumitomo Electric Systems Solutions develop AI for accurate traffic jam prediction: High accuracy mapping with less than 40m of error for one hour in advance

  Science Japan, 電子版, 20 Sep. 2023, Internet

  
• 渋滞長を正確に予測するAI、京大と住友電工システムが開発

  科学新聞, 紙面, 25 Aug. 2023, Paper

  
• AIで渋滞を精密予測 住友電工系 京大など 実運用へ評価試験

  電気新聞, 紙面, 08 Aug. 2023, Paper

  
• 住友電工子会社と京大、渋滞予測の新手法を開発 AIと交通工学で高精度の予測実現

  日刊自動車新聞, 紙面1面・電子版, 08 Aug. 2023, Paper

  

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;バイオロギング;行動認識;階層生物ナビ;ユビキタスコンピューティング;動物行動学;機械学習

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

Education

Teaching subject(s)

• From 01 Apr. 2025, To 31 Mar. 2026

  Computer Science Laboratory and Exercise 1

  9138, Spring, Faculty of Engineering, 2
• From 01 Apr. 2025, To 31 Mar. 2026

  Statistical Learning Theory

  3178, Spring, Graduate School of Informatics, 2
• From 01 Apr. 2025, To 31 Mar. 2026

  Statistical Learning Theory

  M311, Spring, Institute for Liberal Arts and Sciences, 2
• From 01 Apr. 2025, To 31 Mar. 2026

  Statistics and Artificial Intelligence

  N817, Spring, Institute for Liberal Arts and Sciences, 2
• From 01 Apr. 2024, To 31 Mar. 2025

  Computer Science Laboratory and Exercise 1

  9138, Spring, Faculty of Engineering, 2
• From 01 Apr. 2024, To 31 Mar. 2025

  Statistical Learning Theory

  3178, Spring, Graduate School of Informatics, 2
• From 01 Apr. 2024, To 31 Mar. 2025

  Statistical Learning Theory

  M311, Spring, Institute for Liberal Arts and Sciences, 2
• From 01 Apr. 2024, To 31 Mar. 2025

  Statistics and Artificial Intelligence

  N817, Spring, Institute for Liberal Arts and Sciences, 2
• 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. 2024, To 31 Mar. 2026

  計算機小委員会
• From 01 Apr. 2024, To 31 Mar. 2026

  情報セキュリティ作業委員会委員
• From 01 Apr. 2021, To 31 Mar. 2022

  広報WG委員

Academic, Social Contribution

Committee Memberships

• From May 2025, To May 2027

  Board member, The Japanese Society for Artificial Intelligence
• 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