Takuya Konishi

Specially-appointed lecturer

Graduate School of Information Science and Technology

The University of Osaka

Email: konishi[ a t ]ist.osaka-u.ac.jp

Research interests

• Machine learning
• Knowledge discovery and data mining

Publications

• Learning with Almost Invariant Sets in Neural Oscillatory ODEs. Yuto Inui, Takuya Konishi, Yoshinobu Kawahara. ICONIP 2024. [link]
• Stable Invariant Models via Koopman Spectra. Takuya Konishi, Yoshinobu Kawahara. Neural Networks 2023. [link]
• End-to-End Learning for Prediction and Optimization with Gradient Boosting. Takuya Konishi, Takuro Fukunaga. ECML-PKDD 2020. [link]
• Stochastic Submodular Maximization with Performance-Dependent Item Costs. Takuro Fukunaga, Takuya Konishi, Sumio Fujita, Ken-ichi Kawarabayashi. AAAI 2019. [link]
• Identifying Key Observers to Find Popular Information in Advance. Takuya Konishi, Tomoharu Iwata, Kohei Hayashi, Ken-ichi Kawarabayashi. IJCAI 2016. [link]
• Extracting Search Query Patterns via the Pairwise Coupled Topic Model. Takuya Konishi, Takuya Ohwa, Sumio Fujita, Kazushi Ikeda, Kohei Hayashi. WSDM 2016. [link]
• Variational Bayesian Inference Algorithms for Infinite Relational Model of Network Data. Takuya Konishi, Takatomi Kubo, Kazuho Watanabe and Kazushi Ikeda. IEEE TNNLS 2015. [link]
• Topic Model for User Reviews with Adaptive Windows. Takuya Konishi, Fuminori Kimura and Akira Maeda. ECIR 2013 (short paper). [link]
• Estimating Aspects in Online Reviews Using Topic Model with 2-Level Learning. Takuya Konishi, Taro Tezuka, Fuminori Kimura and Akira Maeda. IMECS 2012. [link]

Workshop presentations

• Variational Bayesian Inference Algorithms for Network Infinite Relational Model. Takuya Konishi, Takatomi Kubo, Kazuho Watanabe and Kazushi Ikeda. NIPS 2013 Workshop on Frontiers of Network Analysis: Methods, Models, and Applications. [link]

Preprints

• Explorative Curriculum Learning for Strongly Correlated Electron Systems. Kimihiro Yamazaki, Takuya Konishi, Yoshinobu Kawahara. arXiv:2505.00233. [link]
• A Tractable Fully Bayesian Method for the Stochastic Block Model. Kohei Hayashi, Takuya Konishi, Tatsuro Kawamoto. arXiv:1602.02256. [link]

Work experience

• April 2023 - current. Specially-appointed lecturer at Graduate School of Information Science and Technology, Osaka University.
• April 2021 - current. Visiting scientist at Center for Advanced Intelligence Project, RIKEN.
• April 2022 - March 2023. Assistant professor at Institute of Mathematics for Industry, Kyushu University.
• November 2020 - March 2022. Project assistant professor at Institute of Mathematics for Industry, Kyushu University.
• April 2015 - October 2020. Project researcher at Global Research Center for Big Data Mathematics, National Institute of Informatics.

Education

• April 2012 - March 2015. Ph.D. of Engineering from Graduate School of Information Science, Nara Institute of Science and Technology.
• April 2010 - March 2012. Master of Engineering from Information Science and Engineering, Graduate School of Science and Engineering, Ritsumeikan University.
• April 2006 - March 2010. Bachelor of Engineering from Department of Media Technology, College of Information Science and Engineering, Ritsumeikan University.

Award

• Best Student Paper Award. The 2012 IAENG International Conference on Data Mining and Applications.

Review activities

• AAAI, ACML, AISTATS, ICML, ICLR, IEEE TNNLS, IJCAI, NeurIPS, etc.