6 citations · 20 across the 9 of their papers we have counts for
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cs.LG2020★ 3 cited
On the Rademacher Complexity of Linear Hypothesis Sets
Pranjal Awasthi, Natalie Frank, Mehryar Mohri
Linear predictors form a rich class of hypotheses used in a variety of learning algorithms. We present a tight analysis of the empirical Rademacher complexity of the family of line…
cs.LG2020★ 5 cited
Adversarial Learning Guarantees for Linear Hypotheses and Neural Networks
Pranjal Awasthi, Natalie Frank, Mehryar Mohri
Adversarial or test time robustness measures the susceptibility of a classifier to perturbations to the test input. While there has been a flurry of recent work on designing defens…