Author

Oscar Leong

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Preprint Oct 2026

The Geometry of Anisotropic Dilation for Optimal Regularization

A central question in data-driven inverse problems is how to construct a regularizer that adapts to the geometry of the data distribution. Recent work in optimal regularization shows that, within a broad Gibbs class, the regularizer best matched to a distribution $P$ is determined by a single, direction-dependent radia...

Carson Newman, Oscar Leong · 0 citations

#machine learning Preprint Sep 2026

Entropy Can Flow, or It Can Guide. Be Entropy. LEDFlow: Introducing Entropy-guided Generation Order into Uniform Discrete Flow

Low-Entropy Discrete Flow (LEDFlow), a training-free sampler that adaptively orders absorption by local entropy, is proposed, and it is shown that, under entropy-error regularity, selecting the lowest-entropy positions under a fixed absorption count minimizes an upper bound on the conditional term.

Tung Sum Thomas Kwok, Yi-Dong Ouyang, Yingjia Wan et al. · 0 citations