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cs.LG2023★ 2 cited
The Adversarial Consistency of Surrogate Risks for Binary Classification
Natalie Frank, Jonathan Niles-Weed
We study the consistency of surrogate risks for robust binary classification. It is common to learn robust classifiers by adversarial training, which seeks to minimize the expected…
math.ST2023
Sharp thresholds in inference of planted subgraphs
Elchanan Mossel, Jonathan Niles-Weed, Youngtak Sohn +2
A major question in the study of the Erdős--Rényi random graph is to understand the probability that it contains a given subgraph. This study originated in classical work of Erdős…