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math.ST2026
Any-Dimensional Learning by Sampling
Eitan Levin, Venkat Chandrasekaran
Many machine learning models are defined for inputs of different sizes, such as point clouds containing different numbers of points, sequences of tokens of different lengths, and g…
math.ST2024
Controlling the False Discovery Rate in Subspace Selection
Mateo DÃaz, Venkat Chandrasekaran
Controlling the false discovery rate (FDR) is a popular approach to multiple testing, variable selection, and related problems of simultaneous inference. In many contemporary appli…