Kenji Fukumizu

187 papers A* 32A 10B 6C 2Journal 110Unranked 26

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Fast Flow Matching based Conditional Independence Tests for Causal Discovery. CoRR Shunyu Zhao, Yanfeng Yang, Shuai Li, Kenji Fukumizu
2026	J	`jnl`	Flow Matching from Viewpoint of Proximal Operators. CoRR Kenji Fukumizu, Wei Huang, Han Bao, Shuntuo Xu, Nisha Chandramoothy
2026	—	`conf`	Look Before You Leap: A Lookahead Reasoning Quality Gate for Speculative Decoding. EACL (Volume 1: Long Papers) Hiroaki Kingetsu, Kaoru Yokoo, Kenji Fukumizu, Manohar Kaul
2025	A*	`conf`	Compositional simulation-based inference for time series. ICLR Manuel Glöckler, Shoji Toyota, Kenji Fukumizu, Jakob H. Macke
2025	J	`jnl`	Conditionally Whitened Generative Models for Probabilistic Time Series Forecasting. CoRR Yanfeng Yang, Siwei Chen, Pingping Hu, Zhaotong Shen, Yingjie Zhang, Zhuoran Sun, Shuai Li, Ziqi Chen, Kenji Fukumizu
2025	J	`jnl`	Diffusion Models with Double Guidance: Generate with aggregated datasets. CoRR Yanfeng Yang, Kenji Fukumizu
2025	J	`jnl`	DoubleGen: Debiased Generative Modeling of Counterfactuals. CoRR Alex Luedtke, Kenji Fukumizu
2025	A*	`conf`	Flow matching achieves almost minimax optimal convergence. ICLR Kenji Fukumizu, Taiji Suzuki, Noboru Isobe, Kazusato Oko, Masanori Koyama
2025	J	`jnl`	Generalized Sobolev IPM for Graph-Based Measures. CoRR Tam Le, Truyen Nguyen, Hideitsu Hino, Kenji Fukumizu
2025	J	`jnl`	Orlicz-Sobolev Transport for Unbalanced Measures on a Graph. CoRR Tam Le, Truyen Nguyen, Hideitsu Hino, Kenji Fukumizu
2025	A*	`conf`	Scalable Sobolev IPM for Probability Measures on a Graph. ICML Tam Le, Truyen Nguyen, Hideitsu Hino, Kenji Fukumizu
2025	J	`jnl`	Scalable Sobolev IPM for Probability Measures on a Graph. CoRR Tam Le, Truyen Nguyen, Hideitsu Hino, Kenji Fukumizu
2025	J	`jnl`	Simultaneous Learning of Optimal Transports for Training All-to-All Flow-Based Condition Transfer Model. CoRR Kotaro Ikeda, Masanori Koyama, Jinzhe Zhang, Kohei Hayashi, Kenji Fukumizu
2024	J	`jnl`	Compositional simulation-based inference for time series. CoRR Manuel Glöckler, Shoji Toyota, Kenji Fukumizu, Jakob H. Macke
2024	J	`jnl`	Extended Flow Matching: a Method of Conditional Generation with Generalized Continuity Equation. CoRR Noboru Isobe, Masanori Koyama, Kohei Hayashi, Kenji Fukumizu
2024	J	`jnl`	Flow matching achieves minimax optimal convergence. CoRR Kenji Fukumizu, Taiji Suzuki, Noboru Isobe, Kazusato Oko, Masanori Koyama
2024	A*	`conf`	Generalized Sobolev Transport for Probability Measures on a Graph. ICML Tam Le, Truyen Nguyen, Kenji Fukumizu
2024	J	`jnl`	Generalized Sobolev Transport for Probability Measures on a Graph. CoRR Tam Le, Truyen Nguyen, Kenji Fukumizu
2024	A*	`conf`	Neural Fourier Transform: A General Approach to Equivariant Representation Learning. ICLR Masanori Koyama, Kenji Fukumizu, Kohei Hayashi, Takeru Miyato
2024	A*	`conf`	Neural-Kernel Conditional Mean Embeddings. ICML Eiki Shimizu, Kenji Fukumizu, Dino Sejdinovic
2024	J	`jnl`	Neural-Kernel Conditional Mean Embeddings. CoRR Eiki Shimizu, Kenji Fukumizu, Dino Sejdinovic
2024	A	`conf`	Optimal Transport for Measures with Noisy Tree Metric. AISTATS Tam Le, Truyen Nguyen, Kenji Fukumizu
2024	J	`jnl`	Out-of-Distribution Optimality of Invariant Risk Minimization. Trans. Mach. Learn. Res. Shoji Toyota, Kenji Fukumizu
2024	J	`jnl`	Scaling Law of Sim2Real Transfer Learning in Expanding Computational Materials Databases for Real-World Predictions. CoRR Shunya Minami, Yoshihiro Hayashi, Stephen Wu, Kenji Fukumizu, Hiroki Sugisawa, Masashi Ishii, Isao Kuwajima, Kazuya Shiratori, Ryo Yoshida
2024	J	`jnl`	State-Separated SARSA: A Practical Sequential Decision-Making Algorithm with Recovering Rewards. CoRR Yuto Tanimoto, Kenji Fukumizu
2023	A*	`conf`	Controlling Posterior Collapse by an Inverse Lipschitz Constraint on the Decoder Network. ICML Yuri Kinoshita, Kenta Oono, Kenji Fukumizu, Yuichi Yoshida, Shin-ichi Maeda
2023	J	`jnl`	Controlling Posterior Collapse by an Inverse Lipschitz Constraint on the Decoder Network. CoRR Yuri Kinoshita, Kenta Oono, Kenji Fukumizu, Yuichi Yoshida, Shin-ichi Maeda
2023	J	`jnl`	Neural Fourier Transform: A General Approach to Equivariant Representation Learning. CoRR Masanori Koyama, Kenji Fukumizu, Kohei Hayashi, Takeru Miyato
2023	J	`jnl`	Optimal Transport for Measures with Noisy Tree Metric. CoRR Tam Le, Truyen Nguyen, Kenji Fukumizu
2023	J	`jnl`	Out-of-Distribution Optimality of Invariant Risk Minimization. CoRR Shoji Toyota, Kenji Fukumizu
2023	A	`conf`	Scalable Unbalanced Sobolev Transport for Measures on a Graph. AISTATS Tam Le, Truyen Nguyen, Kenji Fukumizu
2023	J	`jnl`	Scalable Unbalanced Sobolev Transport for Measures on a Graph. CoRR Tam Le, Truyen Nguyen, Kenji Fukumizu
2023	A*	`conf`	Transfer Learning with Affine Model Transformation. NeurIPS Shunya Minami, Kenji Fukumizu, Yoshihiro Hayashi, Ryo Yoshida
2022	A*	`conf`	$\beta$-Intact-VAE: Identifying and Estimating Causal Effects under Limited Overlap. ICLR Pengzhou Abel Wu, Kenji Fukumizu
2022	—	`conf`	A Scaling Law for Syn2real Transfer: How Much Is Your Pre-training Effective? ECML/PKDD (3) Hiroaki Mikami, Kenji Fukumizu, Shogo Murai, Shuji Suzuki, Yuta Kikuchi, Taiji Suzuki, Shin-ichi Maeda, Kohei Hayashi
2022	J	`jnl`	ALGAN: Anomaly Detection by Generating Pseudo Anomalous Data via Latent Variables. IEEE Access Hironori Murase, Kenji Fukumizu
2022	J	`jnl`	ALGAN: Anomaly Detection by Generating Pseudo Anomalous Data via Latent Variables. CoRR Hironori Murase, Kenji Fukumizu
2022	J	`jnl`	Advantage of Deep Neural Networks for Estimating Functions with Singularity on Hypersurfaces. J. Mach. Learn. Res. Masaaki Imaizumi, Kenji Fukumizu
2022	A*	`conf`	Invariance Learning based on Label Hierarchy. NeurIPS Shoji Toyota, Kenji Fukumizu
2022	J	`jnl`	Invariance Learning based on Label Hierarchy. CoRR Shoji Toyota, Kenji Fukumizu
2022	J	`jnl`	Invariance-adapted decomposition and Lasso-type contrastive learning. CoRR Masanori Koyama, Takeru Miyato, Kenji Fukumizu
2022	J	`jnl`	Robust Topological Inference in the Presence of Outliers. CoRR Siddharth Vishwanath, Bharath K. Sriperumbudur, Kenji Fukumizu, Satoshi Kuriki
2022	J	`jnl`	Transfer learning with affine model transformation. CoRR Shunya Minami, Kenji Fukumizu, Yoshihiro Hayashi, Ryo Yoshida
2022	A*	`conf`	Unsupervised Learning of Equivariant Structure from Sequences. NeurIPS Takeru Miyato, Masanori Koyama, Kenji Fukumizu
2022	J	`jnl`	Unsupervised Learning of Equivariant Structure from Sequences. CoRR Takeru Miyato, Masanori Koyama, Kenji Fukumizu
2021	A*	`conf`	A General Class of Transfer Learning Regression without Implementation Cost. AAAI Shunya Minami, Song Liu, Stephen Wu, Kenji Fukumizu, Ryo Yoshida
2021	J	`jnl`	A Scaling Law for Synthetic-to-Real Transfer: A Measure of Pre-Training. CoRR Hiroaki Mikami, Kenji Fukumizu, Shogo Murai, Shuji Suzuki, Yuta Kikuchi, Taiji Suzuki, Shin-ichi Maeda, Kohei Hayashi
2021	J	`jnl`	Convex covariate clustering for classification. Pattern Recognit. Lett. Daniel Andrade, Kenji Fukumizu, Yuzuru Okajima
2021	J	`jnl`	Identifying Treatment Effects under Unobserved Confounding by Causal Representation Learning. CoRR Pengzhou Wu, Kenji Fukumizu
2021	A*	`conf`	Meta Learning for Causal Direction. AAAI Jean-François Ton, Dino Sejdinovic, Kenji Fukumizu
2021	A	`ed.`	The 24th International Conference on Artificial Intelligence and Statistics, AISTATS 2021, April 13-15, 2021, Virtual Event. AISTATS Arindam Banerjee, Kenji Fukumizu
2021	J	`jnl`	Towards Principled Causal Effect Estimation by Deep Identifiable Models. CoRR Pengzhou Wu, Kenji Fukumizu
2021	J	`jnl`	β-Intact-VAE: Identifying and Estimating Causal Effects under Limited Overlap. CoRR Pengzhou Wu, Kenji Fukumizu
2020	J	`jnl`	A General Class of Transfer Learning Regression without Implementation Cost. CoRR Shunya Minami, Song Liu, Stephen Wu, Kenji Fukumizu, Ryo Yoshida
2020	J	`jnl`	A reproducing kernel Hilbert space approach to high dimensional partially varying coefficient model. Comput. Stat. Data Anal. Shaogao Lv, Zengyan Fan, Heng Lian, Taiji Suzuki, Kenji Fukumizu
2020	J	`jnl`	Advantage of Deep Neural Networks for Estimating Functions with Singularity on Curves. CoRR Masaaki Imaizumi, Kenji Fukumizu
2020	A	`conf`	Causal Mosaic: Cause-Effect Inference via Nonlinear ICA and Ensemble Method. AISTATS Pengzhou Wu, Kenji Fukumizu
2020	J	`jnl`	Causal Mosaic: Cause-Effect Inference via Nonlinear ICA and Ensemble Method. CoRR Pengzhou Wu, Kenji Fukumizu
2020	J	`jnl`	Convergence Analysis of Deterministic Kernel-Based Quadrature Rules in Misspecified Settings. Found. Comput. Math. Motonobu Kanagawa, Bharath K. Sriperumbudur, Kenji Fukumizu
2020	—	`conf`	Exchangeable Deep Neural Networks for Set-to-Set Matching and Learning. ECCV (17) Yuki Saito, Takuma Nakamura, Hirotaka Hachiya, Kenji Fukumizu
2020	J	`jnl`	Meta Learning for Causal Direction. CoRR Jean-Francois Ton, Dino Sejdinovic, Kenji Fukumizu
2020	J	`jnl`	Model-based kernel sum rule: kernel Bayesian inference with probabilistic models. Mach. Learn. Yu Nishiyama, Motonobu Kanagawa, Arthur Gretton, Kenji Fukumizu
2020	J	`jnl`	Robust Bayesian model selection for variable clustering with the Gaussian graphical model. Stat. Comput. Daniel Andrade, Akiko Takeda, Kenji Fukumizu
2020	A*	`conf`	Robust Persistence Diagrams using Reproducing Kernels. NeurIPS Siddharth Vishwanath, Kenji Fukumizu, Satoshi Kuriki, Bharath K. Sriperumbudur
2020	J	`jnl`	Robust Persistence Diagrams using Reproducing Kernels. CoRR Siddharth Vishwanath, Kenji Fukumizu, Satoshi Kuriki, Bharath K. Sriperumbudur
2020	A*	`conf`	Smoothness and Stability in GANs. ICLR Casey Chu, Kentaro Minami, Kenji Fukumizu
2020	J	`jnl`	Smoothness and Stability in GANs. CoRR Casey Chu, Kentaro Minami, Kenji Fukumizu
2020	J	`jnl`	The equivalence between Stein variational gradient descent and black-box variational inference. CoRR Casey Chu, Kentaro Minami, Kenji Fukumizu
2020	J	`jnl`	imPhy: Imputing Phylogenetic Trees with Missing Information Using Mathematical Programming. IEEE ACM Trans. Comput. Biol. Bioinform. Niko Yasui, Chrysafis Vogiatzis, Ruriko Yoshida, Kenji Fukumizu
2019	J	`jnl`	A Kernel Stein Test for Comparing Latent Variable Models. CoRR Heishiro Kanagawa, Wittawat Jitkrittum, Lester Mackey, Kenji Fukumizu, Arthur Gretton
2019	A	`conf`	Deep Neural Networks Learn Non-Smooth Functions Effectively. AISTATS Masaaki Imaizumi, Kenji Fukumizu
2019	J	`jnl`	Deep Set-to-Set Matching and Learning. CoRR Yuki Saito, Takuma Nakamura, Hirotaka Hachiya, Kenji Fukumizu
2019	J	`jnl`	Model Selection for Simulator-based Statistical Models: A Kernel Approach. CoRR Takafumi Kajihara, Motonobu Kanagawa, Yuuki Nakaguchi, Kanishka Khandelwal, Kenji Fukumizu
2019	J	`jnl`	Multilocus phylogenetic analysis with gene tree clustering. Ann. Oper. Res. Ruriko Yoshida, Kenji Fukumizu, Chrysafis Vogiatzis
2019	—	`conf`	Post Selection Inference with Incomplete Maximum Mean Discrepancy Estimator. ICLR (Poster) Makoto Yamada, Denny Wu, Yao-Hung Hubert Tsai, Hirofumi Ohta, Ruslan Salakhutdinov, Ichiro Takeuchi, Kenji Fukumizu
2019	A*	`conf`	Semi-flat minima and saddle points by embedding neural networks to overparameterization. NeurIPS Kenji Fukumizu, Shoichiro Yamaguchi, Yoh-ichi Mototake, Mirai Tanaka
2019	J	`jnl`	Semi-flat minima and saddle points by embedding neural networks to overparameterization. CoRR Kenji Fukumizu, Shoichiro Yamaguchi, Yoh-ichi Mototake, Mirai Tanaka
2019	J	`jnl`	Tree-Sliced Approximation of Wasserstein Distances. CoRR Tam Le, Makoto Yamada, Kenji Fukumizu, Marco Cuturi
2019	A*	`conf`	Tree-Sliced Variants of Wasserstein Distances. NeurIPS Tam Le, Makoto Yamada, Kenji Fukumizu, Marco Cuturi
2018	—	`conf`	From Black-Box to White-Box: Interpretable Learning with Kernel Machines. MLDM (1) Hao Zhang, Shinji Nakadai, Kenji Fukumizu
2018	J	`jnl`	Influence function and robust variant of kernel canonical correlation analysis. Neurocomputing Md. Ashad Alam, Kenji Fukumizu, Yu-Ping Wang
2018	A*	`conf`	Kernel Recursive ABC: Point Estimation with Intractable Likelihood. ICML Takafumi Kajihara, Motonobu Kanagawa, Keisuke Yamazaki, Kenji Fukumizu
2018	A*	`conf`	Pointwise HSIC: A Linear-Time Kernelized Co-occurrence Norm for Sparse Linguistic Expressions. EMNLP Sho Yokoi, Sosuke Kobayashi, Kenji Fukumizu, Jun Suzuki, Kentaro Inui
2018	J	`jnl`	Pointwise HSIC: A Linear-Time Kernelized Co-occurrence Norm for Sparse Linguistic Expressions. CoRR Sho Yokoi, Sosuke Kobayashi, Kenji Fukumizu, Jun Suzuki, Kentaro Inui
2018	A	`conf`	Post Selection Inference with Kernels. AISTATS Makoto Yamada, Yuta Umezu, Kenji Fukumizu, Ichiro Takeuchi
2018	—	`conf`	Selecting the Best in GANs Family: a Post Selection Inference Framework. ICLR (Workshop) Yao-Hung Hubert Tsai, Denny Wu, Makoto Yamada, Ruslan Salakhutdinov, Ichiro Takeuchi, Kenji Fukumizu
2018	J	`jnl`	Selecting the Best in GANs Family: a Post Selection Inference Framework. CoRR Yao-Hung Hubert Tsai, Makoto Yamada, Denny Wu, Ruslan Salakhutdinov, Ichiro Takeuchi, Kenji Fukumizu
2018	A*	`conf`	Variational Learning on Aggregate Outputs with Gaussian Processes. NeurIPS Ho Chung Leon Law, Dino Sejdinovic, Ewan Cameron, Tim C. D. Lucas, Seth R. Flaxman, Katherine Battle, Kenji Fukumizu
2018	J	`jnl`	Variational Learning on Aggregate Outputs with Gaussian Processes. CoRR Ho Chung Leon Law, Dino Sejdinovic, Ewan Cameron, Tim C. D. Lucas, Seth R. Flaxman, Katherine Battle, Kenji Fukumizu
2017	J	`jnl`	A Characterization of Minimum Spanning Tree-Like Metric Spaces. IEEE ACM Trans. Comput. Biol. Bioinform. Momoko Hayamizu, Hiroshi Endo, Kenji Fukumizu
2017	—	`conf`	A Linear-Time Kernel Goodness-of-Fit Test. NIPS Wittawat Jitkrittum, Wenkai Xu, Zoltán Szabó, Kenji Fukumizu, Arthur Gretton
2017	J	`jnl`	A Linear-Time Kernel Goodness-of-Fit Test. CoRR Wittawat Jitkrittum, Wenkai Xu, Zoltán Szabó, Kenji Fukumizu, Arthur Gretton
2017	J	`jnl`	Convergence Analysis of Deterministic Kernel-Based Quadrature Rules in Misspecified Settings. CoRR Motonobu Kanagawa, Bharath K. Sriperumbudur, Kenji Fukumizu
2017	J	`jnl`	Density Estimation in Infinite Dimensional Exponential Families. J. Mach. Learn. Res. Bharath K. Sriperumbudur, Kenji Fukumizu, Arthur Gretton, Aapo Hyvärinen, Revant Kumar
2017	J	`jnl`	Kernel Mean Embedding of Distributions: A Review and Beyond. Found. Trends Mach. Learn. Krikamol Muandet, Kenji Fukumizu, Bharath K. Sriperumbudur, Bernhard Schölkopf
2017	J	`jnl`	Kernel Method for Persistence Diagrams via Kernel Embedding and Weight Factor. J. Mach. Learn. Res. Genki Kusano, Kenji Fukumizu, Yasuaki Hiraoka
2017	J	`jnl`	On minimum spanning tree-like metric spaces. Discret. Appl. Math. Momoko Hayamizu, Kenji Fukumizu
2017	—	`conf`	Trimmed Density Ratio Estimation. NIPS Song Liu, Akiko Takeda, Taiji Suzuki, Kenji Fukumizu
2017	J	`jnl`	Unsupervised group matching with application to cross-lingual topic matching without alignment information. Data Min. Knowl. Discov. Tomoharu Iwata, Motonobu Kanagawa, Tsutomu Hirao, Kenji Fukumizu
2016	J	`jnl`	Characteristic Kernels and Infinitely Divisible Distributions. J. Mach. Learn. Res. Yu Nishiyama, Kenji Fukumizu
2016	—	`conf`	Convergence guarantees for kernel-based quadrature rules in misspecified settings. NIPS Motonobu Kanagawa, Bharath K. Sriperumbudur, Kenji Fukumizu
2016	A	`conf`	Estimating Posterior Ratio for Classification: Transfer Learning from Probabilistic Perspective. SDM Song Liu, Kenji Fukumizu
2016	J	`jnl`	Filtering with State-Observation Examples via Kernel Monte Carlo Filter. Neural Comput. Motonobu Kanagawa, Yu Nishiyama, Arthur Gretton, Kenji Fukumizu
2016	A*	`conf`	Flattening the Density Gradient for Eliminating Spatial Centrality to Reduce Hubness. AAAI Kazuo Hara, Ikumi Suzuki, Kei Kobayashi, Kenji Fukumizu, Milos Radovanovic
2016	J	`jnl`	Kernel Mean Embedding of Distributions: A Review and Beyonds. CoRR Krikamol Muandet, Kenji Fukumizu, Bharath K. Sriperumbudur, Bernhard Schölkopf
2016	J	`jnl`	Kernel Mean Shrinkage Estimators. J. Mach. Learn. Res. Krikamol Muandet, Bharath K. Sriperumbudur, Kenji Fukumizu, Arthur Gretton, Bernhard Schölkopf
2016	A*	`conf`	Persistence weighted Gaussian kernel for topological data analysis. ICML Genki Kusano, Yasuaki Hiraoka, Kenji Fukumizu
2016	A*	`conf`	Structure Learning of Partitioned Markov Networks. ICML Song Liu, Taiji Suzuki, Masashi Sugiyama, Kenji Fukumizu
2015	J	`jnl`	A characterization of minimum spanning tree-like metric spaces. CoRR Momoko Hayamizu, Hiroshi Endo, Kenji Fukumizu
2015	J	`jnl`	Computing Functions of Random Variables via Reproducing Kernel Hilbert Space Representations. CoRR Bernhard Schölkopf, Krikamol Muandet, Kenji Fukumizu, Jonas Peters
2015	J	`jnl`	Computing functions of random variables via reproducing kernel Hilbert space representations. Stat. Comput. Bernhard Schölkopf, Krikamol Muandet, Kenji Fukumizu, Stefan Harmeling, Jonas Peters
2015	J	`jnl`	Higher-Order Regularized Kernel Canonical Correlation Analysis. Int. J. Pattern Recognit. Artif. Intell. Md. Ashad Alam, Kenji Fukumizu
2015	J	`jnl`	Kernel-Based Information Criterion. Comput. Inf. Sci. Somayeh Danafar, Kenji Fukumizu, Faustino Gomez
2015	J	`jnl`	Lazy Transfer Learning. CoRR Song Liu, Kenji Fukumizu
2015	A*	`conf`	Localized Centering: Reducing Hubness in Large-Sample Data. AAAI Kazuo Hara, Ikumi Suzuki, Masashi Shimbo, Kei Kobayashi, Kenji Fukumizu, Milos Radovanovic
2015	B	`conf`	Reducing Hubness for Kernel Regression. SISAP Kazuo Hara, Ikumi Suzuki, Kei Kobayashi, Kenji Fukumizu, Milos Radovanovic
2015	A*	`conf`	Reducing Hubness: A Cause of Vulnerability in Recommender Systems. SIGIR Kazuo Hara, Ikumi Suzuki, Kei Kobayashi, Kenji Fukumizu
2014	J	`jnl`	Deep Learning: Theory, Algorithms, and Applications (NII Shonan Meeting 2014-5). NII Shonan Meet. Rep. Pierre Baldi, Kenji Fukumizu, Tomaso A. Poggio
2014	J	`jnl`	Hyperparameter Selection in Kernel Principal Component Analysis. J. Comput. Sci. Md. Ashad Alam, Kenji Fukumizu
2014	A*	`conf`	Kernel Mean Estimation and Stein Effect. ICML Krikamol Muandet, Kenji Fukumizu, Bharath K. Sriperumbudur, Arthur Gretton, Bernhard Schölkopf
2014	J	`jnl`	Kernel Mean Shrinkage Estimators. CoRR Krikamol Muandet, Kenji Fukumizu, Bharath K. Sriperumbudur, Arthur Gretton, Bernhard Schölkopf
2014	A*	`conf`	Monte Carlo Filtering Using Kernel Embedding of Distributions. AAAI Motonobu Kanagawa, Yu Nishiyama, Arthur Gretton, Kenji Fukumizu
2014	A	`conf`	Recovering Distributions from Gaussian RKHS Embeddings. AISTATS Motonobu Kanagawa, Kenji Fukumizu
2013	A*	`conf`	Centering Similarity Measures to Reduce Hubs. EMNLP Ikumi Suzuki, Kazuo Hara, Masashi Shimbo, Marco Saerens, Kenji Fukumizu
2013	—	`conf`	Higher-Order Regularized Kernel CCA. ICMLA (1) Md. Ashad Alam, Kenji Fukumizu
2013	J	`jnl`	Kernel Bayes' rule: Bayesian inference with positive definite kernels. J. Mach. Learn. Res. Kenji Fukumizu, Le Song, Arthur Gretton
2013	J	`jnl`	Kernel Embeddings of Conditional Distributions: A Unified Kernel Framework for Nonparametric Inference in Graphical Models. IEEE Signal Process. Mag. Le Song, Kenji Fukumizu, Arthur Gretton
2013	J	`jnl`	Kernel Mean Estimation and Stein's Effect. CoRR Krikamol Muandet, Kenji Fukumizu, Bharath K. Sriperumbudur, Arthur Gretton, Bernhard Schölkopf
2013	J	`jnl`	Special Issue on Advances in Kernel-Based Learning for Signal Processing [From the Guest Editors]. IEEE Signal Process. Mag. Klaus-Robert Müller, Tülay Adali, Kenji Fukumizu, José C. Príncipe, Sergios Theodoridis
2012	J	`jnl`	Equivalence of distance-based and RKHS-based statistics in hypothesis testing CoRR Dino Sejdinovic, Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu
2012	—	`conf`	Gradient-based kernel method for feature extraction and variable selection. NIPS Kenji Fukumizu, Chenlei Leng
2012	J	`jnl`	Hilbert Space Embeddings of POMDPs CoRR Yu Nishiyama, Abdeslam Boularias, Arthur Gretton, Kenji Fukumizu
2012	A	`conf`	Hilbert Space Embeddings of POMDPs. UAI Yu Nishiyama, Abdeslam Boularias, Arthur Gretton, Kenji Fukumizu
2012	J	`jnl`	Hypothesis testing using pairwise distances and associated kernels (with Appendix) CoRR Dino Sejdinovic, Arthur Gretton, Bharath K. Sriperumbudur, Kenji Fukumizu
2012	A*	`conf`	Hypothesis testing using pairwise distances and associated kernels. ICML Dino Sejdinovic, Arthur Gretton, Bharath K. Sriperumbudur, Kenji Fukumizu
2012	J	`jnl`	Learning from Distributions via Support Measure Machines CoRR Krikamol Muandet, Bernhard Schölkopf, Kenji Fukumizu, Francesco Dinuzzo
2012	—	`conf`	Learning from Distributions via Support Measure Machines. NIPS Krikamol Muandet, Kenji Fukumizu, Francesco Dinuzzo, Bernhard Schölkopf
2012	—	`conf`	Optimal kernel choice for large-scale two-sample tests. NIPS Arthur Gretton, Bharath K. Sriperumbudur, Dino Sejdinovic, Heiko Strathmann, Sivaraman Balakrishnan, Massimiliano Pontil, Kenji Fukumizu
2011	J	`jnl`	Gradient-based kernel dimension reduction for supervised learning CoRR Kenji Fukumizu, Chenlei Leng
2011	—	`conf`	Kernel Bayes' Rule. NIPS Kenji Fukumizu, Le Song, Arthur Gretton
2011	—	`conf`	Learning in Hilbert vs. Banach Spaces: A Measure Embedding Viewpoint. NIPS Bharath K. Sriperumbudur, Kenji Fukumizu, Gert R. G. Lanckriet
2011	C	`conf`	Learning low-rank output kernels. ACML Francesco Dinuzzo, Kenji Fukumizu
2011	J	`jnl`	Loopy Belief Propagation, Bethe Free Energy and Graph Zeta Function CoRR Yusuke Watanabe, Kenji Fukumizu
2011	J	`jnl`	New Graph Polynomials from the Bethe Approximation of the Ising Partition Function. Comb. Probab. Comput. Yusuke Watanabe, Kenji Fukumizu
2011	J	`jnl`	Statistical approaches to combining binary classifiers for multi-class classification. Neurocomputing Yuichi Shiraishi, Kenji Fukumizu
2011	J	`jnl`	Universality, Characteristic Kernels and RKHS Embedding of Measures. J. Mach. Learn. Res. Bharath K. Sriperumbudur, Kenji Fukumizu, Gert R. G. Lanckriet
2010	J	`jnl`	A Comparative Study of Kernel and Robust Canonical Correlation Analysis. J. Multim. Md. Ashad Alam, Mohammed Nasser, Kenji Fukumizu
2010	J	`jnl`	Graph Zeta Function in the Bethe Free Energy and Loopy Belief Propagation CoRR Yusuke Watanabe, Kenji Fukumizu
2010	J	`jnl`	Hilbert Space Embeddings and Metrics on Probability Measures. J. Mach. Learn. Res. Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu, Bernhard Schölkopf, Gert R. G. Lanckriet
2010	B	`conf`	Non-parametric estimation of integral probability metrics. ISIT Bharath K. Sriperumbudur, Kenji Fukumizu, Arthur Gretton, Bernhard Schölkopf, Gert R. G. Lanckriet
2010	A	`conf`	On the relation between universality, characteristic kernels and RKHS embedding of measures. AISTATS Bharath K. Sriperumbudur, Kenji Fukumizu, Gert R. G. Lanckriet
2009	—	`conf`	A Fast, Consistent Kernel Two-Sample Test. NIPS Arthur Gretton, Kenji Fukumizu, Zaïd Harchaoui, Bharath K. Sriperumbudur
2009	J	`jnl`	A note on integral probability metrics and $\phi$-divergences CoRR Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu, Gert R. G. Lanckriet, Bernhard Schölkopf
2009	—	`conf`	Graph Zeta Function in the Bethe Free Energy and Loopy Belief Propagation. NIPS Yusuke Watanabe, Kenji Fukumizu
2009	J	`jnl`	Graph polynomials and approximation of partition functions with Loopy Belief Propagation CoRR Yusuke Watanabe, Kenji Fukumizu
2009	A*	`conf`	Hilbert space embeddings of conditional distributions with applications to dynamical systems. ICML Le Song, Jonathan Huang, Alexander J. Smola, Kenji Fukumizu
2009	—	`conf`	Kernel Choice and Classifiability for RKHS Embeddings of Probability Distributions. NIPS Bharath K. Sriperumbudur, Kenji Fukumizu, Arthur Gretton, Gert R. G. Lanckriet, Bernhard Schölkopf
2009	J	`jnl`	New graph polynomials from the Bethe approximation of the Ising partition function. CoRR Yusuke Watanabe, Kenji Fukumizu
2008	—	`conf`	Characteristic Kernels on Groups and Semigroups. NIPS Kenji Fukumizu, Bharath K. Sriperumbudur, Arthur Gretton, Bernhard Schölkopf
2008	A*	`conf`	Injective Hilbert Space Embeddings of Probability Measures. COLT Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu, Gert R. G. Lanckriet, Bernhard Schölkopf
2008	J	`jnl`	Relation between weight size and degree of over-fitting in neural network regression. Neural Networks Katsuyuki Hagiwara, Kenji Fukumizu
2007	—	`conf`	A Kernel Statistical Test of Independence. NIPS Arthur Gretton, Kenji Fukumizu, Choon Hui Teo, Le Song, Bernhard Schölkopf, Alexander J. Smola
2007	A*	`conf`	A kernel-based causal learning algorithm. ICML Xiaohai Sun, Dominik Janzing, Bernhard Schölkopf, Kenji Fukumizu
2007	C	`conf`	Active Learning for Network Estimation. CIBCB Shotaro Akaho, Kenji Fukumizu
2007	—	`conf`	Kernel Measures of Conditional Dependence. NIPS Kenji Fukumizu, Arthur Gretton, Xiaohai Sun, Bernhard Schölkopf
2007	J	`jnl`	Parameter estimation for von Mises-Fisher distributions. Comput. Stat. Akihiro Tanabe, Kenji Fukumizu, Shigeyuki Oba, Takashi Takenouchi, Shin Ishii
2007	J	`jnl`	Statistical Consistency of Kernel Canonical Correlation Analysis. J. Mach. Learn. Res. Kenji Fukumizu, Francis R. Bach, Arthur Gretton
2006	—	`conf`	Kernels on Structured Objects Through Nested Histograms. NIPS Marco Cuturi, Kenji Fukumizu
2005	J	`jnl`	Multiresolution Kernels CoRR Marco Cuturi, Kenji Fukumizu
2005	J	`jnl`	Semigroup Kernels on Measures. J. Mach. Learn. Res. Marco Cuturi, Kenji Fukumizu, Jean-Philippe Vert
2005	—	`conf`	Statistical Convergence of Kernel CCA. NIPS Kenji Fukumizu, Francis R. Bach, Arthur Gretton
2004	J	`jnl`	Dimensionality Reduction for Supervised Learning with Reproducing Kernel Hilbert Spaces. J. Mach. Learn. Res. Kenji Fukumizu, Francis R. Bach, Michael I. Jordan
2004	B	`conf`	Over-fitting behavior of Gaussian unit under Gaussian noise. IJCNN Katsuyuko Hagiwara, Kenji Fukumizu
2003	—	`conf`	Kernel Dimensionality Reduction for Supervised Learning. NIPS Kenji Fukumizu, Francis R. Bach, Michael I. Jordan
2002	—	`conf`	Critical Lines in Symmetry of Mixture Models and its Application to Component Splitting. NIPS Kenji Fukumizu, Shotaro Akaho, Shun-ichi Amari
2000	J	`jnl`	Adaptive Method of Realizing Natural Gradient Learning for Multilayer Perceptrons. Neural Comput. Shun-ichi Amari, Hyeyoung Park, Kenji Fukumizu
2000	J	`jnl`	Adaptive natural gradient learning algorithms for various stochastic models. Neural Networks Hyeyoung Park, Shun-ichi Amari, Kenji Fukumizu
2000	B	`conf`	An Efficient Learning Algorithm Using Naturla Gradient and Second Order Information of Error Surface. PRICAI Hyeyoung Park, Kenji Fukumizu, Shun-ichi Amari, Yillbyung Lee
2000	J	`jnl`	Local minima and plateaus in hierarchical structures of multilayer perceptrons. Neural Networks Kenji Fukumizu, Shun-ichi Amari
2000	J	`jnl`	Statistical active learning in multilayer perceptrons. IEEE Trans. Neural Networks Learn. Syst. Kenji Fukumizu
1999	B	`conf`	Generalization Error of Limear Neural Networks in Unidentifiable Cases. ALT Kenji Fukumizu
1998	B	`conf`	Effect of Batch Learning in Multilayer Neural Networks. ICONIP Kenji Fukumizu
1998	—	`ch.`	Probabilistic design. Algorithms and Architectures Sumio Watanabe, Kenji Fukumizu
1996	J	`jnl`	A Regularity Condition of the Information Matrix of a Multilayer Perceptron Network. Neural Networks Kenji Fukumizu
1996	J	`jnl`	A network of chaotic elements for information processing. Neural Networks Shin Ishii, Kenji Fukumizu, Sumio Watanabe
1995	—	`conf`	Active Learning in Multilayer Perceptrons. NIPS Kenji Fukumizu
1995	J	`jnl`	Probabilistic design of layered neural networks based on their unified framework. IEEE Trans. Neural Networks Sumio Watanabe, Kenji Fukumizu