Kenji Fukumizu

According to our database, Kenji Fukumizu authored at least 141 papers between 1995 and 2024.

Collaborative distances:

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

2024

State-Separated SARSA: A Practical Sequential Decision-Making Algorithm with Recovering Rewards.

Yuto Tanimoto, Kenji Fukumizu

CoRR, 2024

Neural-Kernel Conditional Mean Embeddings.

Eiki Shimizu, Kenji Fukumizu, Dino Sejdinovic

CoRR, 2024

Extended Flow Matching: a Method of Conditional Generation with Generalized Continuity Equation.

Noboru Isobe, Masanori Koyama, Kohei Hayashi, Kenji Fukumizu

CoRR, 2024

Generalized Sobolev Transport for Probability Measures on a Graph.

Tam Le, Truyen Nguyen, Kenji Fukumizu

CoRR, 2024

2023

Optimal Transport for Measures with Noisy Tree Metric.

Tam Le, Truyen Nguyen, Kenji Fukumizu

CoRR, 2023

Out-of-Distribution Optimality of Invariant Risk Minimization.

Shoji Toyota, Kenji Fukumizu

CoRR, 2023

Neural Fourier Transform: A General Approach to Equivariant Representation Learning.

Masanori Koyama, Kenji Fukumizu, Kohei Hayashi, Takeru Miyato

CoRR, 2023

Transfer Learning with Affine Model Transformation.

Shunya Minami, Kenji Fukumizu, Yoshihiro Hayashi, Ryo Yoshida

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

Controlling Posterior Collapse by an Inverse Lipschitz Constraint on the Decoder Network.

Yuri Kinoshita, Kenta Oono, Kenji Fukumizu, Yuichi Yoshida, Shin-ichi Maeda

Proceedings of the International Conference on Machine Learning, 2023

Scalable Unbalanced Sobolev Transport for Measures on a Graph.

Tam Le, Truyen Nguyen, Kenji Fukumizu

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Advantage of Deep Neural Networks for Estimating Functions with Singularity on Hypersurfaces.

Masaaki Imaizumi, Kenji Fukumizu

J. Mach. Learn. Res., 2022

Invariance-adapted decomposition and Lasso-type contrastive learning.

Masanori Koyama, Takeru Miyato, Kenji Fukumizu

CoRR, 2022

Robust Topological Inference in the Presence of Outliers.

Siddharth Vishwanath, Bharath K. Sriperumbudur, Kenji Fukumizu, Satoshi Kuriki

CoRR, 2022

ALGAN: Anomaly Detection by Generating Pseudo Anomalous Data via Latent Variables.

Hironori Murase, Kenji Fukumizu

IEEE Access, 2022

A Scaling Law for Syn2real Transfer: How Much Is Your Pre-training Effective?

Hiroaki Mikami, Kenji Fukumizu, Shogo Murai, Shuji Suzuki, Yuta Kikuchi, Taiji Suzuki, Shin-ichi Maeda, Kohei Hayashi

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

Invariance Learning based on Label Hierarchy.

Shoji Toyota, Kenji Fukumizu

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Unsupervised Learning of Equivariant Structure from Sequences.

Takeru Miyato, Masanori Koyama, Kenji Fukumizu

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

$\beta$-Intact-VAE: Identifying and Estimating Causal Effects under Limited Overlap.

Pengzhou Abel Wu, Kenji Fukumizu

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Convex covariate clustering for classification.

Daniel Andrade, Kenji Fukumizu, Yuzuru Okajima

Pattern Recognit. Lett., 2021

β-Intact-VAE: Identifying and Estimating Causal Effects under Limited Overlap.

Pengzhou Wu, Kenji Fukumizu

CoRR, 2021

Towards Principled Causal Effect Estimation by Deep Identifiable Models.

Pengzhou Wu, Kenji Fukumizu

CoRR, 2021

A Scaling Law for Synthetic-to-Real Transfer: A Measure of Pre-Training.

Hiroaki Mikami, Kenji Fukumizu, Shogo Murai, Shuji Suzuki, Yuta Kikuchi, Taiji Suzuki, Shin-ichi Maeda, Kohei Hayashi

CoRR, 2021

Identifying Treatment Effects under Unobserved Confounding by Causal Representation Learning.

Pengzhou Wu, Kenji Fukumizu

CoRR, 2021

Meta Learning for Causal Direction.

Jean-François Ton, Dino Sejdinovic, Kenji Fukumizu

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

A General Class of Transfer Learning Regression without Implementation Cost.

Shunya Minami, Song Liu, Stephen Wu, Kenji Fukumizu, Ryo Yoshida

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

imPhy: Imputing Phylogenetic Trees with Missing Information Using Mathematical Programming.

Niko Yasui, Chrysafis Vogiatzis, Ruriko Yoshida, Kenji Fukumizu

IEEE ACM Trans. Comput. Biol. Bioinform., 2020

Robust Bayesian model selection for variable clustering with the Gaussian graphical model.

Daniel Andrade, Akiko Takeda, Kenji Fukumizu

Stat. Comput., 2020

Model-based kernel sum rule: kernel Bayesian inference with probabilistic models.

Yu Nishiyama, Motonobu Kanagawa, Arthur Gretton, Kenji Fukumizu

Mach. Learn., 2020

Convergence Analysis of Deterministic Kernel-Based Quadrature Rules in Misspecified Settings.

Motonobu Kanagawa, Bharath K. Sriperumbudur, Kenji Fukumizu

Found. Comput. Math., 2020

A reproducing kernel Hilbert space approach to high dimensional partially varying coefficient model.

Shaogao Lv, Zengyan Fan, Heng Lian, Taiji Suzuki, Kenji Fukumizu

Comput. Stat. Data Anal., 2020

Advantage of Deep Neural Networks for Estimating Functions with Singularity on Curves.

Masaaki Imaizumi, Kenji Fukumizu

CoRR, 2020

The equivalence between Stein variational gradient descent and black-box variational inference.

Casey Chu, Kentaro Minami, Kenji Fukumizu

CoRR, 2020

Robust Persistence Diagrams using Reproducing Kernels.

Siddharth Vishwanath, Kenji Fukumizu, Satoshi Kuriki, Bharath K. Sriperumbudur

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Smoothness and Stability in GANs.

Casey Chu, Kentaro Minami, Kenji Fukumizu

Proceedings of the 8th International Conference on Learning Representations, 2020

Exchangeable Deep Neural Networks for Set-to-Set Matching and Learning.

Yuki Saito, Takuma Nakamura, Hirotaka Hachiya, Kenji Fukumizu

Proceedings of the Computer Vision - ECCV 2020, 2020

Causal Mosaic: Cause-Effect Inference via Nonlinear ICA and Ensemble Method.

Pengzhou Wu, Kenji Fukumizu

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Deep Set-to-Set Matching and Learning.

Yuki Saito, Takuma Nakamura, Hirotaka Hachiya, Kenji Fukumizu

CoRR, 2019

A Kernel Stein Test for Comparing Latent Variable Models.

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

CoRR, 2019

Model Selection for Simulator-based Statistical Models: A Kernel Approach.

Takafumi Kajihara, Motonobu Kanagawa, Yuuki Nakaguchi, Kanishka Khandelwal, Kenji Fukumizu

CoRR, 2019

Tree-Sliced Approximation of Wasserstein Distances.

Tam Le, Makoto Yamada, Kenji Fukumizu, Marco Cuturi

CoRR, 2019

Multilocus phylogenetic analysis with gene tree clustering.

Ruriko Yoshida, Kenji Fukumizu, Chrysafis Vogiatzis

Ann. Oper. Res., 2019

Tree-Sliced Variants of Wasserstein Distances.

Tam Le, Makoto Yamada, Kenji Fukumizu, Marco Cuturi

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Semi-flat minima and saddle points by embedding neural networks to overparameterization.

Kenji Fukumizu, Shoichiro Yamaguchi, Yoh-ichi Mototake, Mirai Tanaka

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Post Selection Inference with Incomplete Maximum Mean Discrepancy Estimator.

Makoto Yamada, Denny Wu, Yao-Hung Hubert Tsai, Hirofumi Ohta, Ruslan Salakhutdinov, Ichiro Takeuchi, Kenji Fukumizu

Proceedings of the 7th International Conference on Learning Representations, 2019

Deep Neural Networks Learn Non-Smooth Functions Effectively.

Masaaki Imaizumi, Kenji Fukumizu

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Influence function and robust variant of kernel canonical correlation analysis.

Md. Ashad Alam, Kenji Fukumizu, Yu-Ping Wang

Neurocomputing, 2018

Variational Learning on Aggregate Outputs with Gaussian Processes.

Ho Chung Leon Law, Dino Sejdinovic, Ewan Cameron, Tim C. D. Lucas, Seth R. Flaxman, Katherine Battle, Kenji Fukumizu

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

From Black-Box to White-Box: Interpretable Learning with Kernel Machines.

Hao Zhang, Shinji Nakadai, Kenji Fukumizu

Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2018

Kernel Recursive ABC: Point Estimation with Intractable Likelihood.

Takafumi Kajihara, Motonobu Kanagawa, Keisuke Yamazaki, Kenji Fukumizu

Proceedings of the 35th International Conference on Machine Learning, 2018

Selecting the Best in GANs Family: a Post Selection Inference Framework.

Yao-Hung Hubert Tsai, Denny Wu, Makoto Yamada, Ruslan Salakhutdinov, Ichiro Takeuchi, Kenji Fukumizu

Proceedings of the 6th International Conference on Learning Representations, 2018

Pointwise HSIC: A Linear-Time Kernelized Co-occurrence Norm for Sparse Linguistic Expressions.

Sho Yokoi, Sosuke Kobayashi, Kenji Fukumizu, Jun Suzuki, Kentaro Inui

Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

Post Selection Inference with Kernels.

Makoto Yamada, Yuta Umezu, Kenji Fukumizu, Ichiro Takeuchi

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

A Characterization of Minimum Spanning Tree-Like Metric Spaces.

Momoko Hayamizu, Hiroshi Endo, Kenji Fukumizu

IEEE ACM Trans. Comput. Biol. Bioinform., 2017

Density Estimation in Infinite Dimensional Exponential Families.

Bharath K. Sriperumbudur, Kenji Fukumizu, Arthur Gretton, Aapo Hyvärinen, Revant Kumar

J. Mach. Learn. Res., 2017

Kernel Method for Persistence Diagrams via Kernel Embedding and Weight Factor.

Genki Kusano, Kenji Fukumizu, Yasuaki Hiraoka

J. Mach. Learn. Res., 2017

Kernel Mean Embedding of Distributions: A Review and Beyond.

Krikamol Muandet, Kenji Fukumizu, Bharath K. Sriperumbudur, Bernhard Schölkopf

Found. Trends Mach. Learn., 2017

Unsupervised group matching with application to cross-lingual topic matching without alignment information.

Tomoharu Iwata, Motonobu Kanagawa, Tsutomu Hirao, Kenji Fukumizu

Data Min. Knowl. Discov., 2017

On minimum spanning tree-like metric spaces.

Momoko Hayamizu, Kenji Fukumizu

Discret. Appl. Math., 2017

Trimmed Density Ratio Estimation.

Song Liu, Akiko Takeda, Taiji Suzuki, Kenji Fukumizu

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

A Linear-Time Kernel Goodness-of-Fit Test.

Wittawat Jitkrittum, Wenkai Xu, Zoltán Szabó, Kenji Fukumizu, Arthur Gretton

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016

Filtering with State-Observation Examples via Kernel Monte Carlo Filter.

Motonobu Kanagawa, Yu Nishiyama, Arthur Gretton, Kenji Fukumizu

Neural Comput., 2016

Characteristic Kernels and Infinitely Divisible Distributions.

Yu Nishiyama, Kenji Fukumizu

J. Mach. Learn. Res., 2016

Kernel Mean Shrinkage Estimators.

Krikamol Muandet, Bharath K. Sriperumbudur, Kenji Fukumizu, Arthur Gretton, Bernhard Schölkopf

J. Mach. Learn. Res., 2016

Kernel Mean Embedding of Distributions: A Review and Beyonds.

Krikamol Muandet, Kenji Fukumizu, Bharath K. Sriperumbudur, Bernhard Schölkopf

CoRR, 2016

Estimating Posterior Ratio for Classification: Transfer Learning from Probabilistic Perspective.

Song Liu, Kenji Fukumizu

Proceedings of the 2016 SIAM International Conference on Data Mining, 2016

Convergence guarantees for kernel-based quadrature rules in misspecified settings.

Motonobu Kanagawa, Bharath K. Sriperumbudur, Kenji Fukumizu

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

Structure Learning of Partitioned Markov Networks.

Song Liu, Taiji Suzuki, Masashi Sugiyama, Kenji Fukumizu

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

Persistence weighted Gaussian kernel for topological data analysis.

Genki Kusano, Yasuaki Hiraoka, Kenji Fukumizu

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

Flattening the Density Gradient for Eliminating Spatial Centrality to Reduce Hubness.

Kazuo Hara, Ikumi Suzuki, Kei Kobayashi, Kenji Fukumizu, Milos Radovanovic

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

Computing functions of random variables via reproducing kernel Hilbert space representations.

Bernhard Schölkopf, Krikamol Muandet, Kenji Fukumizu, Stefan Harmeling, Jonas Peters

Stat. Comput., 2015

Higher-Order Regularized Kernel Canonical Correlation Analysis.

Md. Ashad Alam, Kenji Fukumizu

Int. J. Pattern Recognit. Artif. Intell., 2015

Computing Functions of Random Variables via Reproducing Kernel Hilbert Space Representations.

Bernhard Schölkopf, Krikamol Muandet, Kenji Fukumizu, Jonas Peters

CoRR, 2015

Lazy Transfer Learning.

Song Liu, Kenji Fukumizu

CoRR, 2015

Kernel-Based Information Criterion.

Somayeh Danafar, Kenji Fukumizu, Faustino Gomez

Comput. Inf. Sci., 2015

Reducing Hubness for Kernel Regression.

Kazuo Hara, Ikumi Suzuki, Kei Kobayashi, Kenji Fukumizu, Milos Radovanovic

Proceedings of the Similarity Search and Applications - 8th International Conference, 2015

Reducing Hubness: A Cause of Vulnerability in Recommender Systems.

Kazuo Hara, Ikumi Suzuki, Kei Kobayashi, Kenji Fukumizu

Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2015

Localized Centering: Reducing Hubness in Large-Sample Data.

Kazuo Hara, Ikumi Suzuki, Masashi Shimbo, Kei Kobayashi, Kenji Fukumizu, Milos Radovanovic

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014

Deep Learning: Theory, Algorithms, and Applications (NII Shonan Meeting 2014-5).

Pierre Baldi, Kenji Fukumizu, Tomaso A. Poggio

NII Shonan Meet. Rep., 2014

Hyperparameter Selection in Kernel Principal Component Analysis.

Md. Ashad Alam, Kenji Fukumizu

J. Comput. Sci., 2014

Kernel Mean Estimation and Stein Effect.

Krikamol Muandet, Kenji Fukumizu, Bharath K. Sriperumbudur, Arthur Gretton, Bernhard Schölkopf

Proceedings of the 31th International Conference on Machine Learning, 2014

Recovering Distributions from Gaussian RKHS Embeddings.

Motonobu Kanagawa, Kenji Fukumizu

Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

Monte Carlo Filtering Using Kernel Embedding of Distributions.

Motonobu Kanagawa, Yu Nishiyama, Arthur Gretton, Kenji Fukumizu

Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013

Kernel Embeddings of Conditional Distributions: A Unified Kernel Framework for Nonparametric Inference in Graphical Models.

Le Song, Kenji Fukumizu, Arthur Gretton

IEEE Signal Process. Mag., 2013

Special Issue on Advances in Kernel-Based Learning for Signal Processing [From the Guest Editors].

Klaus-Robert Müller, Tülay Adali, Kenji Fukumizu, José C. Príncipe, Sergios Theodoridis

IEEE Signal Process. Mag., 2013

Kernel Bayes' rule: Bayesian inference with positive definite kernels.

Kenji Fukumizu, Le Song, Arthur Gretton

J. Mach. Learn. Res., 2013

Kernel Mean Estimation and Stein's Effect.

Krikamol Muandet, Kenji Fukumizu, Bharath K. Sriperumbudur, Arthur Gretton, Bernhard Schölkopf

CoRR, 2013

Higher-Order Regularized Kernel CCA.

Md. Ashad Alam, Kenji Fukumizu

Proceedings of the 12th International Conference on Machine Learning and Applications, 2013

Centering Similarity Measures to Reduce Hubs.

Ikumi Suzuki, Kazuo Hara, Masashi Shimbo, Marco Saerens, Kenji Fukumizu

Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing, 2013

2012

Equivalence of distance-based and RKHS-based statistics in hypothesis testing

Dino Sejdinovic, Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu

CoRR, 2012

Hypothesis testing using pairwise distances and associated kernels (with Appendix)

Dino Sejdinovic, Arthur Gretton, Bharath K. Sriperumbudur, Kenji Fukumizu

CoRR, 2012

Hilbert Space Embeddings of POMDPs.

Yu Nishiyama, Abdeslam Boularias, Arthur Gretton, Kenji Fukumizu

Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

Learning from Distributions via Support Measure Machines.

Krikamol Muandet, Kenji Fukumizu, Francesco Dinuzzo, Bernhard Schölkopf

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Optimal kernel choice for large-scale two-sample tests.

Arthur Gretton, Bharath K. Sriperumbudur, Dino Sejdinovic, Heiko Strathmann, Sivaraman Balakrishnan, Massimiliano Pontil, Kenji Fukumizu

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Gradient-based kernel method for feature extraction and variable selection.

Kenji Fukumizu, Chenlei Leng

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Hypothesis testing using pairwise distances and associated kernels.

Dino Sejdinovic, Arthur Gretton, Bharath K. Sriperumbudur, Kenji Fukumizu

Proceedings of the 29th International Conference on Machine Learning, 2012

2011

Universality, Characteristic Kernels and RKHS Embedding of Measures.

Bharath K. Sriperumbudur, Kenji Fukumizu, Gert R. G. Lanckriet

J. Mach. Learn. Res., 2011

Learning low-rank output kernels.

Francesco Dinuzzo, Kenji Fukumizu

Proceedings of the 3rd Asian Conference on Machine Learning, 2011

Statistical approaches to combining binary classifiers for multi-class classification.

Yuichi Shiraishi, Kenji Fukumizu

Neurocomputing, 2011

New Graph Polynomials from the Bethe Approximation of the Ising Partition Function.

Yusuke Watanabe, Kenji Fukumizu

Comb. Probab. Comput., 2011

Gradient-based kernel dimension reduction for supervised learning

Kenji Fukumizu, Chenlei Leng

CoRR, 2011

Loopy Belief Propagation, Bethe Free Energy and Graph Zeta Function

Yusuke Watanabe, Kenji Fukumizu

CoRR, 2011

Learning in Hilbert vs. Banach Spaces: A Measure Embedding Viewpoint.

Bharath K. Sriperumbudur, Kenji Fukumizu, Gert R. G. Lanckriet

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Kernel Bayes' Rule.

Kenji Fukumizu, Le Song, Arthur Gretton

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

2010

A Comparative Study of Kernel and Robust Canonical Correlation Analysis.

Md. Ashad Alam, Mohammed Nasser, Kenji Fukumizu

J. Multim., 2010

Hilbert Space Embeddings and Metrics on Probability Measures.

Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu, Bernhard Schölkopf, Gert R. G. Lanckriet

J. Mach. Learn. Res., 2010

On the relation between universality, characteristic kernels and RKHS embedding of measures.

Bharath K. Sriperumbudur, Kenji Fukumizu, Gert R. G. Lanckriet

Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Non-parametric estimation of integral probability metrics.

Bharath K. Sriperumbudur, Kenji Fukumizu, Arthur Gretton, Bernhard Schölkopf, Gert R. G. Lanckriet

Proceedings of the IEEE International Symposium on Information Theory, 2010

2009

Graph polynomials and approximation of partition functions with Loopy Belief Propagation

Yusuke Watanabe, Kenji Fukumizu

CoRR, 2009

A note on integral probability metrics and $\phi$-divergences

Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu, Gert R. G. Lanckriet, Bernhard Schölkopf

CoRR, 2009

Graph Zeta Function in the Bethe Free Energy and Loopy Belief Propagation.

Yusuke Watanabe, Kenji Fukumizu

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Kernel Choice and Classifiability for RKHS Embeddings of Probability Distributions.

Bharath K. Sriperumbudur, Kenji Fukumizu, Arthur Gretton, Gert R. G. Lanckriet, Bernhard Schölkopf

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

A Fast, Consistent Kernel Two-Sample Test.

Arthur Gretton, Kenji Fukumizu, Zaïd Harchaoui, Bharath K. Sriperumbudur

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Hilbert space embeddings of conditional distributions with applications to dynamical systems.

Le Song, Jonathan Huang, Alexander J. Smola, Kenji Fukumizu

Proceedings of the 26th Annual International Conference on Machine Learning, 2009

2008

Relation between weight size and degree of over-fitting in neural network regression.

Katsuyuki Hagiwara, Kenji Fukumizu

Neural Networks, 2008

Characteristic Kernels on Groups and Semigroups.

Kenji Fukumizu, Bharath K. Sriperumbudur, Arthur Gretton, Bernhard Schölkopf

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Injective Hilbert Space Embeddings of Probability Measures.

Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu, Gert R. G. Lanckriet, Bernhard Schölkopf

Proceedings of the 21st Annual Conference on Learning Theory, 2008

2007

Statistical Consistency of Kernel Canonical Correlation Analysis.

Kenji Fukumizu, Francis R. Bach, Arthur Gretton

J. Mach. Learn. Res., 2007

Parameter estimation for von Mises-Fisher distributions.

Akihiro Tanabe, Kenji Fukumizu, Shigeyuki Oba, Takashi Takenouchi, Shin Ishii

Comput. Stat., 2007

A Kernel Statistical Test of Independence.

Arthur Gretton, Kenji Fukumizu, Choon Hui Teo, Le Song, Bernhard Schölkopf, Alexander J. Smola

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Kernel Measures of Conditional Dependence.

Kenji Fukumizu, Arthur Gretton, Xiaohai Sun, Bernhard Schölkopf

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

A kernel-based causal learning algorithm.

Xiaohai Sun, Dominik Janzing, Bernhard Schölkopf, Kenji Fukumizu

Proceedings of the Machine Learning, 2007

Active Learning for Network Estimation.

Shotaro Akaho, Kenji Fukumizu

Proceedings of the 2007 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, 2007

2006

Kernels on Structured Objects Through Nested Histograms.

Marco Cuturi, Kenji Fukumizu

Proceedings of the Advances in Neural Information Processing Systems 19, 2006

2005

Semigroup Kernels on Measures.

Marco Cuturi, Kenji Fukumizu, Jean-Philippe Vert

J. Mach. Learn. Res., 2005

Multiresolution Kernels

Marco Cuturi, Kenji Fukumizu

CoRR, 2005

Statistical Convergence of Kernel CCA.

Kenji Fukumizu, Francis R. Bach, Arthur Gretton

Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

2004

Dimensionality Reduction for Supervised Learning with Reproducing Kernel Hilbert Spaces.

Kenji Fukumizu, Francis R. Bach, Michael I. Jordan

J. Mach. Learn. Res., 2004

2003

Kernel Dimensionality Reduction for Supervised Learning.

Kenji Fukumizu, Francis R. Bach, Michael I. Jordan

Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

2002

Critical Lines in Symmetry of Mixture Models and its Application to Component Splitting.

Kenji Fukumizu, Shotaro Akaho, Shun-ichi Amari

Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

2000

Statistical active learning in multilayer perceptrons.

Kenji Fukumizu

IEEE Trans. Neural Networks Learn. Syst., 2000

Adaptive natural gradient learning algorithms for various stochastic models.

Hyeyoung Park, Shun-ichi Amari, Kenji Fukumizu

Neural Networks, 2000

Local minima and plateaus in hierarchical structures of multilayer perceptrons.

Kenji Fukumizu, Shun-ichi Amari

Neural Networks, 2000

Adaptive Method of Realizing Natural Gradient Learning for Multilayer Perceptrons.

Shun-ichi Amari, Hyeyoung Park, Kenji Fukumizu

Neural Comput., 2000

An Efficient Learning Algorithm Using Naturla Gradient and Second Order Information of Error Surface.

Hyeyoung Park, Kenji Fukumizu, Shun-ichi Amari, Yillbyung Lee

Proceedings of the PRICAI 2000, Topics in Artificial Intelligence, 6th Pacific Rim International Conference on Artificial Intelligence, Melbourne, Australia, August 28, 2000

1999

Generalization Error of Limear Neural Networks in Unidentifiable Cases.

Kenji Fukumizu

Proceedings of the Algorithmic Learning Theory, 10th International Conference, 1999

1998

Effect of Batch Learning in Multilayer Neural Networks.

Kenji Fukumizu

Proceedings of the Fifth International Conference on Neural Information Processing, 1998

Probabilistic design.

Sumio Watanabe, Kenji Fukumizu

Proceedings of the Algorithms and Architectures., 1998

1996

A network of chaotic elements for information processing.

Shin Ishii, Kenji Fukumizu, Sumio Watanabe

Neural Networks, 1996

A Regularity Condition of the Information Matrix of a Multilayer Perceptron Network.

Kenji Fukumizu

Neural Networks, 1996

1995

Probabilistic design of layered neural networks based on their unified framework.

Sumio Watanabe, Kenji Fukumizu

IEEE Trans. Neural Networks, 1995

Active Learning in Multilayer Perceptrons.

Kenji Fukumizu

Proceedings of the Advances in Neural Information Processing Systems 8, 1995