Heishiro Kanagawa

21 papers A* 6A 2Journal 11Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Harnessing the Power of Reinforcement Learning for Adaptive MCMC. CoRR Congye Wang, Matthew A. Fisher, Heishiro Kanagawa, Wilson Ye Chen, Chris J. Oates
2025	A	`conf`	Reinforcement Learning for Adaptive MCMC. AISTATS Congye Wang, Wilson Ye Chen, Heishiro Kanagawa, Chris J. Oates
2025	J	`jnl`	Stationary MMD Points for Cubature. CoRR Zonghao Chen, Toni Karvonen, Heishiro Kanagawa, François-Xavier Briol, Chris J. Oates
2024	J	`jnl`	Reinforcement Learning for Adaptive MCMC. CoRR Congye Wang, Wilson Ye Chen, Heishiro Kanagawa, Chris J. Oates
2023	A*	`conf`	A Kernel Stein Test of Goodness of Fit for Sequential Models. ICML Jerome Baum, Heishiro Kanagawa, Arthur Gretton
2023	A*	`conf`	Stein Π-Importance Sampling. NeurIPS Congye Wang, Wilson Ye Chen, Heishiro Kanagawa, Chris J. Oates
2022	J	`jnl`	A kernel Stein test of goodness of fit for sequential models. CoRR Jerome Baum, Heishiro Kanagawa, Arthur Gretton
2022	J	`jnl`	Controlling Moments with Kernel Stein Discrepancies. CoRR Heishiro Kanagawa, Arthur Gretton, Lester Mackey
2021	A*	`conf`	Deep Proxy Causal Learning and its Application to Confounded Bandit Policy Evaluation. NeurIPS Liyuan Xu, Heishiro Kanagawa, Arthur Gretton
2021	J	`jnl`	Deep Proxy Causal Learning and its Application to Confounded Bandit Policy Evaluation. CoRR Liyuan Xu, Heishiro Kanagawa, Arthur Gretton
2020	A*	`conf`	Amortised Learning by Wake-Sleep. ICML Li K. Wenliang, Theodore H. Moskovitz, Heishiro Kanagawa, Maneesh Sahani
2020	J	`jnl`	Amortised Learning by Wake-Sleep. CoRR Li Kevin Wenliang, Theodore H. Moskovitz, Heishiro Kanagawa, Maneesh Sahani
2020	A	`conf`	Testing Goodness of Fit of Conditional Density Models with Kernels. UAI Wittawat Jitkrittum, Heishiro Kanagawa, Bernhard Schölkopf
2020	J	`jnl`	Testing Goodness of Fit of Conditional Density Models with Kernels. CoRR Wittawat Jitkrittum, Heishiro Kanagawa, Bernhard Schölkopf
2019	J	`jnl`	A Kernel Stein Test for Comparing Latent Variable Models. CoRR Heishiro Kanagawa, Wittawat Jitkrittum, Lester Mackey, Kenji Fukumizu, Arthur Gretton
2019	—	`conf`	Cross-Domain Recommendation via Deep Domain Adaptation. ECIR (2) Heishiro Kanagawa, Hayato Kobayashi, Nobuyuki Shimizu, Yukihiro Tagami, Taiji Suzuki
2018	J	`jnl`	Cross-domain Recommendation via Deep Domain Adaptation. CoRR Heishiro Kanagawa, Hayato Kobayashi, Nobuyuki Shimizu, Yukihiro Tagami, Taiji Suzuki
2018	A*	`conf`	Informative Features for Model Comparison. NeurIPS Wittawat Jitkrittum, Heishiro Kanagawa, Patsorn Sangkloy, James Hays, Bernhard Schölkopf, Arthur Gretton
2018	J	`jnl`	Informative Features for Model Comparison. CoRR Wittawat Jitkrittum, Heishiro Kanagawa, Patsorn Sangkloy, James Hays, Bernhard Schölkopf, Arthur Gretton
2016	A*	`conf`	Gaussian process nonparametric tensor estimator and its minimax optimality. ICML Heishiro Kanagawa, Taiji Suzuki, Hayato Kobayashi, Nobuyuki Shimizu, Yukihiro Tagami
2016	—	`conf`	Minimax Optimal Alternating Minimization for Kernel Nonparametric Tensor Learning. NIPS Taiji Suzuki, Heishiro Kanagawa, Hayato Kobayashi, Nobuyuki Shimizu, Yukihiro Tagami