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cs.LG2026
Transport Clustering: Solving Low-Rank Optimal Transport via Clustering
Henri Schmidt, Peter Halmos, Ben Raphael
Optimal transport (OT) finds a least cost transport plan between two probability distributions using a cost matrix defined on pairs of points. Unlike standard OT, which infers unst…
cs.LG2025
Hierarchical Refinement: Optimal Transport to Infinity and Beyond
Peter Halmos, Julian Gold, Xinhao Liu +1
Optimal transport (OT) has enjoyed great success in machine learning as a principled way to align datasets via a least-cost correspondence, driven in large part by the runtime effi…
cs.LG2024★ 1 cited
Low-Rank Optimal Transport through Factor Relaxation with Latent Coupling
Peter Halmos, Xinhao Liu, Julian Gold +1
Optimal transport (OT) is a general framework for finding a minimum-cost transport plan, or coupling, between probability distributions, and has many applications in machine learni…