Yamada, Makoto

57 publications

ICLR 2025 Fast Unsupervised Ground Metric Learning with Tree-Wasserstein Distance Kira Michaela Düsterwald, Samo Hromadka, Makoto Yamada

ICLR 2025 Learning Structured Representations by Embedding Class Hierarchy with Fast Optimal Transport Siqi Zeng, Sixian Du, Makoto Yamada, Han Zhao

TMLR 2025 Necessary and Sufficient Watermark for Large Language Models Yuki Takezawa, Ryoma Sato, Han Bao, Kenta Niwa, Makoto Yamada

ICLRW 2025 On Verbalized Confidence Scores for LLMs Daniel Yang, Yao-Hung Hubert Tsai, Makoto Yamada

ICLR 2025 PhiNets: Brain-Inspired Non-Contrastive Learning Based on Temporal Prediction Hypothesis Satoki Ishikawa, Makoto Yamada, Han Bao, Yuki Takezawa

AISTATS 2024 Fast 1-Wasserstein Distance Approximations Using Greedy Strategies Guillaume Houry, Han Bao, Han Zhao, Makoto Yamada

WACV 2024 Implicit Neural Representation for Change Detection Peter Naylor, Diego Di Carlo, Arianna Traviglia, Makoto Yamada, Marco Fiorucci

NeurIPS 2024 Learning Structured Representations with Hyperbolic Embeddings Aditya Sinha, Siqi Zeng, Makoto Yamada, Han Zhao

NeurIPS 2024 Parameter-Free Clipped Gradient Descent Meets Polyak Yuki Takezawa, Han Bao, Ryoma Sato, Kenta Niwa, Makoto Yamada

TMLR 2024 Stealthy Backdoor Attack via Confidence-Driven Sampling Pengfei He, Yue Xing, Han Xu, Jie Ren, Yingqian Cui, Shenglai Zeng, Jiliang Tang, Makoto Yamada, Mohammad Sabokrou

ICLR 2024 Structural Fairness-Aware Active Learning for Graph Neural Networks Haoyu Han, Xiaorui Liu, Li Ma, MohamadAli Torkamani, Hui Liu, Jiliang Tang, Makoto Yamada

NeurIPSW 2024 Towards the Effect of Examples on In-Context Learning: A Theoretical Case Study Pengfei He, Yingqian Cui, Han Xu, Hui Liu, Makoto Yamada, Jiliang Tang, Yue Xing

ICMLW 2024 Unsupervised Ground Metric Learning with Tree Wasserstein Distance Kira Michaela Düsterwald, Makoto Yamada

NeurIPS 2023 Beyond Exponential Graph: Communication-Efficient Topologies for Decentralized Learning via Finite-Time Convergence Yuki Takezawa, Ryoma Sato, Han Bao, Kenta Niwa, Makoto Yamada

TMLR 2023 Momentum Tracking: Momentum Acceleration for Decentralized Deep Learning on Heterogeneous Data Yuki Takezawa, Han Bao, Kenta Niwa, Ryoma Sato, Makoto Yamada

AISTATS 2023 Nyström Method for Accurate and Scalable Implicit Differentiation Ryuichiro Hataya, Makoto Yamada

ICLR 2023 Robust Graph Dictionary Learning Weijie Liu, Jiahao Xie, Chao Zhang, Makoto Yamada, Nenggan Zheng, Hui Qian

AISTATS 2022 Feature Screening with Kernel Knockoffs Benjamin Poignard, Peter J. Naylor, Héctor Climente-González, Makoto Yamada

AISTATS 2022 Fixed Support Tree-Sliced Wasserstein Barycenter Yuki Takezawa, Ryoma Sato, Zornitsa Kozareva, Sujith Ravi, Makoto Yamada

TMLR 2022 Approximating 1-Wasserstein Distance with Trees Makoto Yamada, Yuki Takezawa, Ryoma Sato, Han Bao, Zornitsa Kozareva, Sujith Ravi

UAI 2022 Feature Selection for Discovering Distributional Treatment Effect Modifiers Yoichi Chikahara, Makoto Yamada, Hisashi Kashima

ECML-PKDD 2022 Feature-Robust Optimal Transport for High-Dimensional Data Mathis Petrovich, Chao Liang, Ryoma Sato, Yanbin Liu, Yao-Hung Hubert Tsai, Linchao Zhu, Yi Yang, Ruslan Salakhutdinov, Makoto Yamada

ICML 2022 Re-Evaluating Word Mover’s Distance Ryoma Sato, Makoto Yamada, Hisashi Kashima

AISTATS 2021 Flow-Based Alignment Approaches for Probability Measures in Different Spaces Tam Le, Nhat Ho, Makoto Yamada

NeurIPS 2021 Adversarial Regression with Doubly Non-Negative Weighting Matrices Tam Le, Truyen Nguyen, Makoto Yamada, Jose Blanchet, Viet Anh Nguyen

NeurIPS 2021 Dynamic Sasvi: Strong Safe Screening for Norm-Regularized Least Squares Hiroaki Yamada, Makoto Yamada

ECML-PKDD 2021 LSMI-Sinkhorn: Semi-Supervised Mutual Information Estimation with Optimal Transport Yanbin Liu, Makoto Yamada, Yao-Hung Hubert Tsai, Tam Le, Ruslan Salakhutdinov, Yi Yang

ICML 2021 Optimal Transport Kernels for Sequential and Parallel Neural Architecture Search Vu Nguyen, Tam Le, Makoto Yamada, Michael A. Osborne

ICML 2021 Post-Selection Inference with HSIC-Lasso Tobias Freidling, Benjamin Poignard, Héctor Climente-González, Makoto Yamada

ICML 2021 Supervised Tree-Wasserstein Distance Yuki Takezawa, Ryoma Sato, Makoto Yamada

NeurIPS 2020 Fast Unbalanced Optimal Transport on a Tree Ryoma Sato, Makoto Yamada, Hisashi Kashima

AISTATS 2020 More Powerful Selective Kernel Tests for Feature Selection Jen Ning Lim, Makoto Yamada, Wittawat Jitkrittum, Yoshikazu Terada, Shigeyuki Matsui, Hidetoshi Shimodaira

NeurIPS 2020 Neural Methods for Point-Wise Dependency Estimation Yao-Hung Hubert Tsai, Han Zhao, Makoto Yamada, Louis-Philippe Morency, Ruslan Salakhutdinov

AISTATS 2020 Sparse Hilbert-Schmidt Independence Criterion Regression Benjamin Poignard, Makoto Yamada

AAAI 2020 Unsupervised Nonlinear Feature Selection from High-Dimensional Signed Networks Qiang Huang, Tingyu Xia, Huiyan Sun, Makoto Yamada, Yi Chang

NeurIPS 2019 Approximation Ratios of Graph Neural Networks for Combinatorial Problems Ryoma Sato, Makoto Yamada, Hisashi Kashima

NeurIPS 2019 Kernel Stein Tests for Multiple Model Comparison Jen Ning Lim, Makoto Yamada, Bernhard Schölkopf, Wittawat Jitkrittum

ACML 2019 Learning to Sample Hard Instances for Graph Algorithms Ryoma Sato, Makoto Yamada, Hisashi Kashima

ICLR 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

NeurIPS 2019 Tree-Sliced Variants of Wasserstein Distances Tam Le, Makoto Yamada, Kenji Fukumizu, Marco Cuturi

NeurIPS 2018 Persistence Fisher Kernel: A Riemannian Manifold Kernel for Persistence Diagrams Tam Le, Makoto Yamada

AISTATS 2018 Post Selection Inference with Kernels Makoto Yamada, Yuta Umezu, Kenji Fukumizu, Ichiro Takeuchi

AISTATS 2017 Localized Lasso for High-Dimensional Regression Makoto Yamada, Koh Takeuchi, Tomoharu Iwata, John Shawe-Taylor, Samuel Kaski

IJCAI 2016 A Robust Convex Formulation for Ensemble Clustering Junning Gao, Makoto Yamada, Samuel Kaski, Hiroshi Mamitsuka, Shanfeng Zhu

NeurIPS 2016 Multi-View Anomaly Detection via Robust Probabilistic Latent Variable Models Tomoharu Iwata, Makoto Yamada

IJCAI 2016 Timeline Summarization from Social Media with Life Cycle Models Yi Chang, Jiliang Tang, Dawei Yin, Makoto Yamada, Yan Liu

AISTATS 2015 Consistent Collective Matrix Completion Under Joint Low Rank Structure Suriya Gunasekar, Makoto Yamada, Dawei Yin, Yi Chang

MLJ 2014 Least-Squares Independence Regression for Non-Linear Causal Inference Under Non-Gaussian Noise Makoto Yamada, Masashi Sugiyama, Jun Sese

IJCAI 2013 Change-Point Detection with Feature Selection in High-Dimensional Time-Series Data Makoto Yamada, Akisato Kimura, Futoshi Naya, Hiroshi Sawada

ICML 2012 Information-Theoretic Semi-Supervised Metric Learning via Entropy Regularization Gang Niu, Bo Dai, Makoto Yamada, Masashi Sugiyama

ECCV 2012 No Bias Left Behind: Covariate Shift Adaptation for Discriminative 3D Pose Estimation Makoto Yamada, Leonid Sigal, Michalis Raptis

ACML 2011 Computationally Efficient Sufficient Dimension Reduction via Squared-Loss Mutual Information Makoto Yamada, Gang Niu, Jun Takagi, Masashi Sugiyama

AISTATS 2011 Cross-Domain Object Matching with Model Selection Makoto Yamada, Masashi Sugiyama

AAAI 2011 Direct Density-Ratio Estimation with Dimensionality Reduction via Hetero-Distributional Subspace Analysis Makoto Yamada, Masashi Sugiyama

ICML 2011 On Information-Maximization Clustering: Tuning Parameter Selection and Analytic Solution Masashi Sugiyama, Makoto Yamada, Manabu Kimura, Hirotaka Hachiya

NeurIPS 2011 Relative Density-Ratio Estimation for Robust Distribution Comparison Makoto Yamada, Taiji Suzuki, Takafumi Kanamori, Hirotaka Hachiya, Masashi Sugiyama

AAAI 2010 Dependence Minimizing Regression with Model Selection for Non-Linear Causal Inference Under Non-Gaussian Noise Makoto Yamada, Masashi Sugiyama