Takeshi Teshima - researchr alias

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Viewing Publication 1 - 7 from 7

2021

γ-ABC: Outlier-Robust Approximate Bayesian Computation Based on a Robust Divergence EstimatorMasahiro Fujisawa, Takeshi Teshima, Issei Sato, Masashi Sugiyama. aistats 2021: 1783-1791 [doi]

Non-Negative Bregman Divergence Minimization for Deep Direct Density Ratio EstimationMasahiro Kato, Takeshi Teshima. icml 2021: 5320-5333 [doi]

Incorporating causal graphical prior knowledge into predictive modeling via simple data augmentationTakeshi Teshima, Masashi Sugiyama. uai 2021: 86-96 [doi]

2020

Coupling-based Invertible Neural Networks Are Universal Diffeomorphism ApproximatorsTakeshi Teshima, Isao Ishikawa, Koichi Tojo, Kenta Oono, Masahiro Ikeda, Masashi Sugiyama. nips 2020: [doi]

Few-shot Domain Adaptation by Causal Mechanism TransferTakeshi Teshima, Issei Sato, Masashi Sugiyama. icml 2020: 9458-9469 [doi]

2019

Learning from Positive and Unlabeled Data with a Selection BiasMasahiro Kato, Takeshi Teshima, Junya Honda. iclr 2019: [doi]

Clipped Matrix Completion: A Remedy for Ceiling EffectsTakeshi Teshima, Miao Xu, Issei Sato, Masashi Sugiyama. AAAI 2019: 5151-5158 [doi]

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