Takeshi Teshima

Publication Activity (10 Years)

Years Active: 2018-2022
Publications (10 Years): 16

Top Topics

Bregman Divergences

Transfer Learning

Domain Adaptation

Top Venues

Publications

Isao Ishikawa, Takeshi Teshima, Koichi Tojo, Kenta Oono, Masahiro Ikeda, Masashi Sugiyama
Universal approximation property of invertible neural networks. CoRR (2022)
Takeshi Teshima, Masashi Sugiyama
Incorporating Causal Graphical Prior Knowledge into Predictive Modeling via Simple Data Augmentation. CoRR (2021)
Masahiro Kato, Takeshi Teshima
Non-Negative Bregman Divergence Minimization for Deep Direct Density Ratio Estimation. ICML (2021)
Takeshi Teshima, Masashi Sugiyama
Incorporating causal graphical prior knowledge into predictive modeling via simple data augmentation. UAI (2021)
Nan Lu, Tianyi Zhang, Tongtong Fang, Takeshi Teshima, Masashi Sugiyama
Rethinking Importance Weighting for Transfer Learning. CoRR (2021)
Masahiro Fujisawa, Takeshi Teshima, Issei Sato, Masashi Sugiyama
γ-ABC: Outlier-Robust Approximate Bayesian Computation Based on a Robust Divergence Estimator. AISTATS (2021)
Takeshi Teshima, Isao Ishikawa, Koichi Tojo, Kenta Oono, Masahiro Ikeda, Masashi Sugiyama
Coupling-based Invertible Neural Networks Are Universal Diffeomorphism Approximators. NeurIPS (2020)
Takeshi Teshima, Koichi Tojo, Masahiro Ikeda, Isao Ishikawa, Kenta Oono
Universal Approximation Property of Neural Ordinary Differential Equations. CoRR (2020)
Masahiro Fujisawa, Takeshi Teshima, Issei Sato
γ-ABC: Outlier-Robust Approximate Bayesian Computation based on Robust Divergence Estimator. CoRR (2020)
Takeshi Teshima, Issei Sato, Masashi Sugiyama
Few-shot Domain Adaptation by Causal Mechanism Transfer. CoRR (2020)
Takeshi Teshima, Issei Sato, Masashi Sugiyama
Few-shot Domain Adaptation by Causal Mechanism Transfer. ICML (2020)
Takeshi Teshima, Isao Ishikawa, Koichi Tojo, Kenta Oono, Masahiro Ikeda, Masashi Sugiyama
Coupling-based Invertible Neural Networks Are Universal Diffeomorphism Approximators. CoRR (2020)
Masahiro Kato, Takeshi Teshima
Non-Negative Bregman Divergence Minimization for Deep Direct Density Ratio Estimation. CoRR (2020)
Takeshi Teshima, Miao Xu, Issei Sato, Masashi Sugiyama
Clipped Matrix Completion: A Remedy for Ceiling Effects. AAAI (2019)
Masahiro Kato, Takeshi Teshima, Junya Honda
Learning from Positive and Unlabeled Data with a Selection Bias. ICLR (Poster) (2019)
Takeshi Teshima, Miao Xu, Issei Sato, Masashi Sugiyama
Clipped Matrix Completion: a Remedy for Ceiling Effects. CoRR (2018)