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Kenji Fukumizu

Publication record assembled from the DBLP archive of ranked conferences.

Papers indexed

45

Venues

19

Active years

1998–2026

Best venue rank

A*

Where they publish

Papers

45 indexed papers, newest first.

YearVenueTitleAuthors
2026EACLLook Before You Leap: A Lookahead Reasoning Quality Gate for Speculative Decoding.Hiroaki Kingetsu, Kaoru Yokoo, Kenji Fukumizu, Manohar Kaul
2025ICLRFlow matching achieves almost minimax optimal convergence.Kenji Fukumizu, Taiji Suzuki, Noboru Isobe, Kazusato Oko, Masanori Koyama
2025ICLRCompositional simulation-based inference for time series.Manuel Glckler, Shoji Toyota, Kenji Fukumizu, Jakob H. Macke
2025ICMLScalable Sobolev IPM for Probability Measures on a Graph.Tam Le, Truyen Nguyen, Hideitsu Hino, Kenji Fukumizu
2024AISTATSOptimal Transport for Measures with Noisy Tree Metric.Tam Le, Truyen Nguyen, Kenji Fukumizu
2024ICLRNeural Fourier Transform: A General Approach to Equivariant Representation Learning.Masanori Koyama, Kenji Fukumizu, Kohei Hayashi, Takeru Miyato
2024ICMLGeneralized Sobolev Transport for Probability Measures on a Graph.Tam Le, Truyen Nguyen, Kenji Fukumizu
2024ICMLNeural-Kernel Conditional Mean Embeddings.Eiki Shimizu, Kenji Fukumizu, Dino Sejdinovic
2023AISTATSScalable Unbalanced Sobolev Transport for Measures on a Graph.Tam Le, Truyen Nguyen, Kenji Fukumizu
2023ICMLControlling Posterior Collapse by an Inverse Lipschitz Constraint on the Decoder Network.Yuri Kinoshita, Kenta Oono, Kenji Fukumizu, Yuichi Yoshida, Shin-ichi Maeda
2022ICLR$\beta$-Intact-VAE: Identifying and Estimating Causal Effects under Limited Overlap.Pengzhou Abel Wu, Kenji Fukumizu
2021AAAIA General Class of Transfer Learning Regression without Implementation Cost.Shunya Minami, Song Liu, Stephen Wu, Kenji Fukumizu, Ryo Yoshida
2021AAAIMeta Learning for Causal Direction.Jean-Franois Ton, Dino Sejdinovic, Kenji Fukumizu
2020AISTATSCausal Mosaic: Cause-Effect Inference via Nonlinear ICA and Ensemble Method.Pengzhou Wu, Kenji Fukumizu
2020ECCVExchangeable Deep Neural Networks for Set-to-Set Matching and Learning.Yuki Saito, Takuma Nakamura, Hirotaka Hachiya, Kenji Fukumizu
2020ICLRSmoothness and Stability in GANs.Casey Chu, Kentaro Minami, Kenji Fukumizu
2019AISTATSDeep Neural Networks Learn Non-Smooth Functions Effectively.Masaaki Imaizumi, Kenji Fukumizu
2019ICLRPost Selection Inference with Incomplete Maximum Mean Discrepancy Estimator.Makoto Yamada, Denny Wu, Yao-Hung Hubert Tsai, Hirofumi Ohta, Ruslan Salakhutdinov, Ichiro Takeuchi, Kenji Fukumizu
2018AISTATSPost Selection Inference with Kernels.Makoto Yamada, Yuta Umezu, Kenji Fukumizu, Ichiro Takeuchi
2018EMNLPPointwise HSIC: A Linear-Time Kernelized Co-occurrence Norm for Sparse Linguistic Expressions.Sho Yokoi, Sosuke Kobayashi, Kenji Fukumizu, Jun Suzuki, Kentaro Inui
2018ICLRSelecting the Best in GANs Family: a Post Selection Inference Framework.Yao-Hung Hubert Tsai, Denny Wu, Makoto Yamada, Ruslan Salakhutdinov, Ichiro Takeuchi, Kenji Fukumizu
2018ICMLKernel Recursive ABC: Point Estimation with Intractable Likelihood.Takafumi Kajihara, Motonobu Kanagawa, Keisuke Yamazaki, Kenji Fukumizu
2016AAAIFlattening the Density Gradient for Eliminating Spatial Centrality to Reduce Hubness.Kazuo Hara, Ikumi Suzuki, Kei Kobayashi, Kenji Fukumizu, Milos Radovanovic
2016ICMLPersistence weighted Gaussian kernel for topological data analysis.Genki Kusano, Yasuaki Hiraoka, Kenji Fukumizu
2016ICMLStructure Learning of Partitioned Markov Networks.Song Liu, Taiji Suzuki, Masashi Sugiyama, Kenji Fukumizu
2016SDMEstimating Posterior Ratio for Classification: Transfer Learning from Probabilistic Perspective.Song Liu, Kenji Fukumizu
2015AAAILocalized Centering: Reducing Hubness in Large-Sample Data.Kazuo Hara, Ikumi Suzuki, Masashi Shimbo, Kei Kobayashi, Kenji Fukumizu, Milos Radovanovic
2015SIGIRReducing Hubness: A Cause of Vulnerability in Recommender Systems.Kazuo Hara, Ikumi Suzuki, Kei Kobayashi, Kenji Fukumizu
2015SISAPReducing Hubness for Kernel Regression.Kazuo Hara, Ikumi Suzuki, Kei Kobayashi, Kenji Fukumizu, Milos Radovanovic
2014AAAIMonte Carlo Filtering Using Kernel Embedding of Distributions.Motonobu Kanagawa, Yu Nishiyama, Arthur Gretton, Kenji Fukumizu
2014AISTATSRecovering Distributions from Gaussian RKHS Embeddings.Motonobu Kanagawa, Kenji Fukumizu
2014ICMLKernel Mean Estimation and Stein Effect.Krikamol Muandet, Kenji Fukumizu, Bharath K. Sriperumbudur, Arthur Gretton, Bernhard Schlkopf
2013EMNLPCentering Similarity Measures to Reduce Hubs.Ikumi Suzuki, Kazuo Hara, Masashi Shimbo, Marco Saerens, Kenji Fukumizu
2013ICMLAHigher-Order Regularized Kernel CCA.Md. Ashad Alam, Kenji Fukumizu
2012ICMLHypothesis testing using pairwise distances and associated kernels.Dino Sejdinovic, Arthur Gretton, Bharath K. Sriperumbudur, Kenji Fukumizu
2012UAIHilbert Space Embeddings of POMDPs.Yu Nishiyama, Abdeslam Boularias, Arthur Gretton, Kenji Fukumizu
2010ISITNon-parametric estimation of integral probability metrics.Bharath K. Sriperumbudur, Kenji Fukumizu, Arthur Gretton, Bernhard Schlkopf, Gert R. G. Lanckriet
2009ICMLHilbert space embeddings of conditional distributions with applications to dynamical systems.Le Song, Jonathan Huang, Alexander J. Smola, Kenji Fukumizu
2008COLTInjective Hilbert Space Embeddings of Probability Measures.Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu, Gert R. G. Lanckriet, Bernhard Schlkopf
2007CIBCBActive Learning for Network Estimation.Shotaro Akaho, Kenji Fukumizu
2007ICMLA kernel-based causal learning algorithm.Xiaohai Sun, Dominik Janzing, Bernhard Schlkopf, Kenji Fukumizu
2004IJCNNOver-fitting behavior of Gaussian unit under Gaussian noise.Katsuyuko Hagiwara, Kenji Fukumizu
2000PRICAIAn Efficient Learning Algorithm Using Naturla Gradient and Second Order Information of Error Surface.Hyeyoung Park, Kenji Fukumizu, Shun-ichi Amari, Yillbyung Lee
1999ALTGeneralization Error of Limear Neural Networks in Unidentifiable Cases.Kenji Fukumizu
1998ICONIPEffect of Batch Learning in Multilayer Neural Networks.Kenji Fukumizu