← Authors

Makoto Yamada

53 papers · 2011–2025 · 15 conferences · across top CS/AI conferences

Achievements

๐Ÿƒ Academic Marathon (14) ๐ŸŒ‰ Interdisciplinary Bridge ๐Ÿ Cross-Pollinator (14) ๐Ÿฃ Hot Topic Early Bird ๐ŸŒˆ Renaissance Researcher (5) ๐ŸŒ Conference Polyglot (15) ๐Ÿ—บ๏ธ Taxonomy Completionist (17) ๐Ÿงญ Keyword Pioneer ๐Ÿ”ฌ Deep Specialist (13) ๐Ÿ† Grand Slam ๐Ÿ† Keyword Champion (4) ๐Ÿ—ƒ๏ธ Keyword Collector (223) โšก Prolific Year (7) ๐Ÿš€ Conference Pioneer ๐Ÿ’Ž Century Club (53) ๐Ÿ”ฅ Unstoppable (11) ๐Ÿ“ˆ Trend Setter โ“ The Questioner

Conferences

NIPS (13) AISTATS (11) EMNLP (6) ICLR (6) ICML (4) IJCAI (3) ACML (2) AAAI (1) ACL (1) CVPR (1) EACL (1) IJCNLP (1) NAACL (1) UAI (1) WACV (1)

Top co-authors

Ryoma Sato (8) Hisashi Kashima (6) Yuki Takezawa (6) Han Zhao (5) Tam Le (5) Yao-Hung Hubert Tsai (5) Han Bao (4) Jiliang Tang (4) Ruslan Salakhutdinov (4) Siqi Zeng (3)

Research topics

Optimization (1)

Keywords

optimal transport (11) kernel methods (11) feature selection (6) wasserstein distance (5) tree metric (4) hilbert-schmidt independence criterion (4) unsupervised learning (3) attention mechanism (3) word mover distance (3) representation learning (3) post-selection inference (2) sequence prediction (2) positional embedding (2) sliced wasserstein (2) false discovery rate (2) mutual information (2) distribution comparison (2) neural machine translation (2) hyperparameter optimization (2) feature importance (2)

Papers

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