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Nys-Curve: Nyström-Approximated Curvature for Stochastic Optimization


Oct 16, 2021
Hardik Tankaria, Dinesh Singh, Makoto Yamada


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Adversarial Regression with Doubly Non-negative Weighting Matrices


Sep 30, 2021
Tam Le, Truyen Nguyen, Makoto Yamada, Jose Blanchet, Viet Anh Nguyen

* Accepted to the Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS2021) 

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Fixed Support Tree-Sliced Wasserstein Barycenter


Sep 08, 2021
Yuki Takezawa, Ryoma Sato, Zornitsa Kozareva, Sujith Ravi, Makoto Yamada


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Re-evaluating Word Mover's Distance


May 30, 2021
Ryoma Sato, Makoto Yamada, Hisashi Kashima


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Computationally Efficient Wasserstein Loss for Structured Labels


Mar 01, 2021
Ayato Toyokuni, Sho Yokoi, Hisashi Kashima, Makoto Yamada


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Dynamic Sasvi: Strong Safe Screening for Norm-Regularized Least Squares


Feb 08, 2021
Hiroaki Yamada, Makoto Yamada


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Supervised Tree-Wasserstein Distance


Jan 27, 2021
Yuki Takezawa, Ryoma Sato, Makoto Yamada


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Post-selection inference with HSIC-Lasso


Oct 29, 2020
Tobias Freidling, Benjamin Poignard, Héctor Climente-González, Makoto Yamada


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Poincare: Recommending Publication Venues via Treatment Effect Estimation


Oct 19, 2020
Ryoma Sato, Makoto Yamada, Hisashi Kashima


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Feature Robust Optimal Transport for High-dimensional Data


Jun 16, 2020
Mathis Petrovich, Chao Liang, Yanbin Liu, Yao-Hung Hubert Tsai, Linchao Zhu, Yi Yang, Ruslan Salakhutdinov, Makoto Yamada


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Optimal Transport Kernels for Sequential and Parallel Neural Architecture Search


Jun 13, 2020
Vu Nguyen, Tam Le, Makoto Yamada, Michael A Osborne

* 21 pages 

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Neural Methods for Point-wise Dependency Estimation


Jun 11, 2020
Yao-Hung Hubert Tsai, Han Zhao, Makoto Yamada, Louis-Philippe Morency, Ruslan Salakhutdinov


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Fast Unbalanced Optimal Transport on Tree


Jun 04, 2020
Ryoma Sato, Makoto Yamada, Hisashi Kashima

* 20 pages 

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Volumization as a Natural Generalization of Weight Decay


Apr 01, 2020
Liu Ziyin, Zihao Wang, Makoto Yamada, Masahito Ueda

* 18 pages, 20 figures 

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Random Features Strengthen Graph Neural Networks


Mar 15, 2020
Ryoma Sato, Makoto Yamada, Hisashi Kashima


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Fast local linear regression with anchor regularization


Feb 21, 2020
Mathis Petrovich, Makoto Yamada


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Fast and Robust Comparison of Probability Measures in Heterogeneous Spaces


Feb 08, 2020
Ryoma Sato, Marco Cuturi, Makoto Yamada, Hisashi Kashima


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FsNet: Feature Selection Network on High-dimensional Biological Data


Jan 23, 2020
Dinesh Singh, Makoto Yamada


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GraphLIME: Local Interpretable Model Explanations for Graph Neural Networks


Jan 17, 2020
Qiang Huang, Makoto Yamada, Yuan Tian, Dinesh Singh, Dawei Yin, Yi Chang


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Kernel Stein Tests for Multiple Model Comparison


Oct 27, 2019
Jen Ning Lim, Makoto Yamada, Bernhard Schölkopf, Wittawat Jitkrittum

* Accepted to NeurIPS 2019 

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More Powerful Selective Kernel Tests for Feature Selection


Oct 14, 2019
Jen Ning Lim, Makoto Yamada, Wittawat Jitkrittum, Yoshikazu Terada, Shigeyuki Matsui, Hidetoshi Shimodaira


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On Scalable Variant of Wasserstein Barycenter


Oct 10, 2019
Tam Le, Viet Huynh, Nhat Ho, Dinh Phung, Makoto Yamada

* Tam Le, Viet Huynh, and Nhat Ho contributed equally to this work 

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Computationally Efficient Tree Variants of Gromov-Wasserstein


Oct 10, 2019
Tam Le, Nhat Ho, Makoto Yamada

* Tam Le and Nhat Ho contributed equally to this work 

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LSMI-Sinkhorn: Semi-supervised Squared-Loss Mutual Information Estimation with Optimal Transport


Sep 05, 2019
Yanbin Liu, Makoto Yamada, Yao-Hung Hubert Tsai, Tam Le, Ruslan Salakhutdinov, Yi Yang

* 14 pages 

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Transformer Dissection: An Unified Understanding for Transformer's Attention via the Lens of Kernel


Aug 30, 2019
Yao-Hung Hubert Tsai, Shaojie Bai, Makoto Yamada, Louis-Philippe Morency, Ruslan Salakhutdinov

* EMNLP 2019 

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