3 papers
stat.ML2026
Preconditioned Regularized Wasserstein Proximal Sampling
Hong Ye Tan, Stanley Osher, Wuchen Li
We consider sampling from a Gibbs distribution by evolving finitely many particles. We propose a preconditioned version of a recently proposed noise-free sampling method, governed…
cs.LG2026
Dataset Distillation as Pushforward Optimal Quantization
Hong Ye Tan, Emma Slade
Dataset distillation aims to find a synthetic training set such that training on the synthetic data achieves similar performance to training on real data, with orders of magnitude…
stat.ML2026
Accelerated Regularized Wasserstein Proximal Sampling Algorithms
Hong Ye Tan, Stanley Osher, Wuchen Li
We consider sampling from a Gibbs distribution by evolving a finite number of particles using a particular score estimator rather than Brownian motion. To accelerate the particles,…