Takuya Konishi

According to our database, Takuya Konishi authored at least 11 papers between 2013 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Predictive Fair Representation Learning with Variational Autoencoders.

Tatsuya Yamada, Takuya Konishi, Yoshinobu Kawahara

New Gener. Comput., May, 2026

Physics-inspired transformer quantum states via latent imaginary-time evolution.

Kimihiro Yamazaki, Itsushi Sakata, Takuya Konishi, Yoshinobu Kawahara

CoRR, February, 2026

2025

Explorative Curriculum Learning for Strongly Correlated Electron Systems.

Kimihiro Yamazaki, Takuya Konishi, Yoshinobu Kawahara

CoRR, May, 2025

2023

Stable invariant models via Koopman spectra.

Takuya Konishi, Yoshinobu Kawahara

Neural Networks, August, 2023

2020

End-to-End Learning for Prediction and Optimization with Gradient Boosting.

Takuya Konishi, Takuro Fukunaga

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020

2019

Stochastic Submodular Maximization with Performance-Dependent Item Costs.

Takuro Fukunaga, Takuya Konishi, Sumio Fujita, Ken-ichi Kawarabayashi

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2016

A Tractable Fully Bayesian Method for the Stochastic Block Model.

Kohei Hayashi, Takuya Konishi, Tatsuro Kawamoto

CoRR, 2016

Extracting Search Query Patterns via the Pairwise Coupled Topic Model.

Takuya Konishi, Takuya Ohwa, Sumio Fujita, Kazushi Ikeda, Kohei Hayashi

Proceedings of the Ninth ACM International Conference on Web Search and Data Mining, 2016

Identifying Key Observers to Find Popular Information in Advance.

Takuya Konishi, Tomoharu Iwata, Kohei Hayashi, Ken-ichi Kawarabayashi

Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

2015

Variational Bayesian Inference Algorithms for Infinite Relational Model of Network Data.

Takuya Konishi, Takatomi Kubo, Kazuho Watanabe, Kazushi Ikeda

IEEE Trans. Neural Networks Learn. Syst., 2015

2013

Topic Model for User Reviews with Adaptive Windows.

Takuya Konishi, Fuminori Kimura, Akira Maeda

Proceedings of the Advances in Information Retrieval, 2013