4 papers
Learning with Monotone Adversarial Corruptions
Kasper Green Larsen, Chirag Pabbaraju, Abhishek Shetty
We study the extent to which standard machine learning algorithms rely on exchangeability and independence of data by introducing a monotone adversarial corruption model. In this m…
Attention Is Not All You Need for Diffraction
Elizabeth J. Baggett, Edward G. Friedman, Abhishek Shetty +5
Determining crystal symmetry from powder X-ray diffraction is a central problem in materials characterization, yet multiple space groups can produce indistinguishable patterns, mak…
Low-Rank Thinning
Annabelle Michael Carrell, Albert Gong, Abhishek Shetty +2
The goal in thinning is to summarize a dataset using a small set of representative points. Remarkably, sub-Gaussian thinning algorithms like Kernel Halving and Compress can match t…
Dimension-Free Correlated Sampling for the Hypersimplex
Joseph, Naor, Nitya Raju +4
Sampling from multiple distributions so as to maximize overlap has been studied by statisticians since the 1950s. Since the 2000s, such correlated sampling from the probability sim…