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stat.ML2025
Precise asymptotic analysis of Sobolev training for random feature models
Katharine E Fisher, Matthew TC Li, Youssef Marzouk +1
Gradient information is widely useful and available in applications, and is therefore natural to include in the training of neural networks. Yet little is known theoretically about…
stat.ML2024
Sharp detection of low-dimensional structure in probability measures via dimensional logarithmic Sobolev inequalities
Matthew T. C. Li, Tiangang Cui, Fengyi Li +2
Identifying low-dimensional structure in high-dimensional probability measures is an essential pre-processing step for efficient sampling. We introduce a method for identifying and…