Kanagawa, Motonobu

11 publications

TMLR 2025 kNNSampler: Stochastic Imputations for Recovering Missing Value Distributions Parastoo Pashmchi, Jérôme Benoit, Motonobu Kanagawa

TMLR 2024 Fast Computation of Leave-One-Out Cross-Validation for $k$-NN Regression Motonobu Kanagawa

JMLR 2024 Improved Random Features for Dot Product Kernels Jonas Wacker, Motonobu Kanagawa, Maurizio Filippone

JMLR 2021 Counterfactual Mean Embeddings Krikamol Muandet, Motonobu Kanagawa, Sorawit Saengkyongam, Sanparith Marukatat

MLJ 2020 Model-Based Kernel Sum Rule: Kernel Bayesian Inference with Probabilistic Models Yu Nishiyama, Motonobu Kanagawa, Arthur Gretton, Kenji Fukumizu

AISTATS 2020 Simulator Calibration Under Covariate Shift with Kernels Keiichi Kisamori, Motonobu Kanagawa, Keisuke Yamazaki

NeurIPS 2019 Convergence Guarantees for Adaptive Bayesian Quadrature Methods Motonobu Kanagawa, Philipp Hennig

ICML 2018 Kernel Recursive ABC: Point Estimation with Intractable Likelihood Takafumi Kajihara, Motonobu Kanagawa, Keisuke Yamazaki, Kenji Fukumizu

NeurIPS 2016 Convergence Guarantees for Kernel-Based Quadrature Rules in Misspecified Settings Motonobu Kanagawa, Bharath K. Sriperumbudur, Kenji Fukumizu

AAAI 2014 Monte Carlo Filtering Using Kernel Embedding of Distributions Motonobu Kanagawa, Yu Nishiyama, Arthur Gretton, Kenji Fukumizu

AISTATS 2014 Recovering Distributions from Gaussian RKHS Embeddings Motonobu Kanagawa, Kenji Fukumizu