← Authors

Tam Le

25 papers · 2013–2025 · 8 conferences · across top CS/AI conferences

Achievements

🌈 Renaissance Researcher (5) 🐝 Cross-Pollinator (12) 🐣 Hot Topic Early Bird πŸ—ΊοΈ Taxonomy Completionist (28) πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (8) πŸƒ Academic Marathon (12) 🧭 Keyword Pioneer 🧬 Topic Evolution πŸ† Keyword Champion (2) πŸ—ƒοΈ Keyword Collector (75) πŸ’Ž Century Club (25) πŸ”₯ Unstoppable (5) πŸ“ˆ Trend Setter ⚑ Prolific Year (7)

Conferences

ICML (8) AISTATS (5) ICLR (4) NIPS (4) ACML (1) CLEAR (1) ICCV (1) IJCAI (1)

Top co-authors

Truyen Nguyen (8) Kenji Fukumizu (5) Makoto Yamada (5) Tan Minh Nguyen (4) Huyen Trang Pham (4) Thanh Chu (4) Hoang V. Tran (4) nhαΊ­t Hα»“ (3) Marco Cuturi (3) Viet Anh Nguyen (3)

Keywords

optimal transport (8) kernel methods (4) probability measure (3) tree metric (3) topological data analysis (2) graph metric (2) unbalanced transport (2) hyperparameter tuning (2) tree metrics (2) wasserstein distance (2) negative definite kernel (2) probability metrics (1) neural architecture search (1) sliced wasserstein distance (1) robust optimization (1) generative modeling (1) fisher kernel (1) convex loss (1) matrix factorization (1) metric learning (1)

Papers

Distance-Based Tree-Sliced Wasserstein Distance ICLR 2025
Tree-Sliced Wasserstein Distance with Nonlinear Projection ICML 2025
Scalable Sobolev IPM for Probability Measures on a Graph ICML 2025
Spherical Tree-Sliced Wasserstein Distance ICLR 2025
Universal generalization guarantees for Wasserstein distributionally robust models ICLR 2025
Tree-Sliced Wasserstein Distance: A Geometric Perspective ICML 2025
SAVA: Scalable Learning-Agnostic Data Valuation ICLR 2025
Scalable Counterfactual Distribution Estimation in Multivariate Causal Models CLEAR 2024
Sliced Wasserstein with Random-Path Projecting Directions ICML 2024
Generalized Sobolev Transport for Probability Measures on a Graph ICML 2024
Optimal Transport for Measures with Noisy Tree Metric AISTATS 2024
Dynamic Flows on Curved Space Generated by Labeled Data IJCAI 2023
Scalable Unbalanced Sobolev Transport for Measures on a Graph AISTATS 2023
Sobolev Transport: A Scalable Metric for Probability Measures with Graph Metrics AISTATS 2022
Flow-based Alignment Approaches for Probability Measures in Different Spaces AISTATS 2021
Point-Set Distances for Learning Representations of 3D Point Clouds ICCV 2021
Optimal Transport Kernels for Sequential and Parallel Neural Architecture Search ICML 2021
Entropy Partial Transport with Tree Metrics: Theory and Practice AISTATS 2021
Adversarial Regression with Doubly Non-negative Weighting Matrices NIPS 2021
Nonsmooth Implicit Differentiation for Machine-Learning and Optimization NIPS 2021
Safe Grid Search with Optimal Complexity ICML 2019
Tree-Sliced Variants of Wasserstein Distances NIPS 2019
Persistence Fisher Kernel: A Riemannian Manifold Kernel for Persistence Diagrams NIPS 2018
Unsupervised Riemannian Metric Learning for Histograms Using Aitchison Transformations ICML 2015
Generalized Aitchison Embeddings for Histograms ACML 2013