Heishiro Kanagawa

According to our database, Heishiro Kanagawa authored at least 12 papers between 2016 and 2024.

Collaborative distances:

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

2024

Reinforcement Learning for Adaptive MCMC.

Congye Wang, Wilson Ye Chen, Heishiro Kanagawa, Chris J. Oates

CoRR, 2024

2023

Stein Π-Importance Sampling.

Congye Wang, Ye Chen, Heishiro Kanagawa, Chris J. Oates

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Kernel Stein Test of Goodness of Fit for Sequential Models.

Jerome Baum, Heishiro Kanagawa, Arthur Gretton

Proceedings of the International Conference on Machine Learning, 2023

2022

Controlling Moments with Kernel Stein Discrepancies.

Heishiro Kanagawa, Arthur Gretton, Lester Mackey

CoRR, 2022

2021

Deep Proxy Causal Learning and its Application to Confounded Bandit Policy Evaluation.

Liyuan Xu, Heishiro Kanagawa, Arthur Gretton

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Testing Goodness of Fit of Conditional Density Models with Kernels.

Wittawat Jitkrittum, Heishiro Kanagawa, Bernhard Schölkopf

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Amortised Learning by Wake-Sleep.

Li K. Wenliang, Theodore H. Moskovitz, Heishiro Kanagawa, Maneesh Sahani

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

A Kernel Stein Test for Comparing Latent Variable Models.

Heishiro Kanagawa, Wittawat Jitkrittum, Lester Mackey, Kenji Fukumizu, Arthur Gretton

CoRR, 2019

Cross-Domain Recommendation via Deep Domain Adaptation.

Heishiro Kanagawa, Hayato Kobayashi, Nobuyuki Shimizu, Yukihiro Tagami, Taiji Suzuki

Proceedings of the Advances in Information Retrieval, 2019

2018

Informative Features for Model Comparison.

Wittawat Jitkrittum, Heishiro Kanagawa, Patsorn Sangkloy, James Hays, Bernhard Schölkopf, Arthur Gretton

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2016

Minimax Optimal Alternating Minimization for Kernel Nonparametric Tensor Learning.

Taiji Suzuki, Heishiro Kanagawa, Hayato Kobayashi, Nobuyuki Shimizu, Yukihiro Tagami

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Gaussian process nonparametric tensor estimator and its minimax optimality.

Heishiro Kanagawa, Taiji Suzuki, Hayato Kobayashi, Nobuyuki Shimizu, Yukihiro Tagami

Proceedings of the 33nd International Conference on Machine Learning, 2016