Makoto Yamada

Data Poisoning for In-context Learning NAACL 2025 Fast unsupervised ground metric learning with tree-Wasserstein distance ICLR 2025 Learning Structured Representations by Embedding Class Hierarchy with Fast Optimal Transport ICLR 2025 PhiNets: Brain-inspired Non-contrastive Learning Based on Temporal Prediction Hypothesis ICLR 2025 When LRP Diverges from Leave-One-Out in Transformers EMNLP 2025 Fast 1-Wasserstein distance approximations using greedy strategies AISTATS 2024 Implicit Neural Representation for Change Detection WACV 2024 Learning Structured Representations with Hyperbolic Embeddings NeurIPS 2024 Parameter-free Clipped Gradient Descent Meets Polyak NeurIPS 2024 Structural Fairness-aware Active Learning for Graph Neural Networks ICLR 2024 Towards Understanding Jailbreak Attacks in LLMs: A Representation Space Analysis EMNLP 2024 A linear time approximation of Wasserstein distance with word embedding selection EMNLP 2023 Beyond Exponential Graph: Communication-Efficient Topologies for Decentralized Learning via Finite-time Convergence NeurIPS 2023 Large-scale similarity search with Optimal Transport EMNLP 2023 Nyström Method for Accurate and Scalable Implicit Differentiation AISTATS 2023 Robust Graph Dictionary Learning ICLR 2023 Feature screening with kernel knockoffs AISTATS 2022 Feature selection for discovering distributional treatment effect modifiers UAI 2022 Fixed Support Tree-Sliced Wasserstein Barycenter AISTATS 2022 Re-evaluating Word Mover’s Distance ICML 2022 Adversarial Regression with Doubly Non-negative Weighting Matrices NeurIPS 2021 Computationally Efficient Wasserstein Loss for Structured Labels EACL 2021 Dynamic Sasvi: Strong Safe Screening for Norm-Regularized Least Squares NeurIPS 2021 Flow-based Alignment Approaches for Probability Measures in Different Spaces AISTATS 2021 Optimal Transport Kernels for Sequential and Parallel Neural Architecture Search ICML 2021 Post-selection inference with HSIC-Lasso ICML 2021 Supervised Tree-Wasserstein Distance ICML 2021 Fast Unbalanced Optimal Transport on a Tree NeurIPS 2020 More Powerful Selective Kernel Tests for Feature Selection AISTATS 2020 Neural Methods for Point-wise Dependency Estimation NeurIPS 2020 Semantic Correspondence as an Optimal Transport Problem CVPR 2020 Sparse Hilbert-Schmidt Independence Criterion Regression AISTATS 2020 Unsupervised Nonlinear Feature Selection from High-Dimensional Signed Networks AAAI 2020 Approximation Ratios of Graph Neural Networks for Combinatorial Problems NeurIPS 2019 Kernel Stein Tests for Multiple Model Comparison NeurIPS 2019 Learning to Sample Hard Instances for Graph Algorithms ACML 2019 Post Selection Inference with Incomplete Maximum Mean Discrepancy Estimator ICLR 2019 Transformer Dissection: An Unified Understanding for Transformer’s Attention via the Lens of Kernel EMNLP 2019 Tree-Sliced Variants of Wasserstein Distances NeurIPS 2019 Learning Unsupervised Word Translations Without Adversaries EMNLP 2018 Persistence Fisher Kernel: A Riemannian Manifold Kernel for Persistence Diagrams NeurIPS 2018 Post Selection Inference with Kernels AISTATS 2018 Localized Lasso for High-Dimensional Regression AISTATS 2017 A Robust Convex Formulation for Ensemble Clustering IJCAI 2016 Multi-view Anomaly Detection via Robust Probabilistic Latent Variable Models NeurIPS 2016 Timeline Summarization from Social Media with Life Cycle Models IJCAI 2016 Which Tumblr Post Should I Read Next? ACL 2016 Consistent Collective Matrix Completion under Joint Low Rank Structure AISTATS 2015 Change-Point Detection with Feature Selection in High-Dimensional Time-Series Data IJCAI 2013 Computationally Efficient Sufficient Dimension Reduction via Squared-Loss Mutual Information ACML 2011 Cross-Domain Object Matching with Model Selection AISTATS 2011 Relative Density-Ratio Estimation for Robust Distribution Comparison NeurIPS 2011