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06/13/2023
Theoretical Foundations of Adversarially Robust Learning
Despite extraordinary progress, current machine learning systems have be...
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05/25/2023
Strategic Classification under Unknown Personalized Manipulation
We study the fundamental mistake bound and sample complexity in the stra...
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09/15/2022
Adversarially Robust Learning: A Generic Minimax Optimal Learner and Characterization
We present a minimax optimal learner for the problem of learning predict...
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02/15/2022
A Theory of PAC Learnability under Transformation Invariances
Transformation invariances are present in many real-world problems. For ...
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10/20/2021
Transductive Robust Learning Guarantees
We study the problem of adversarially robust learning in the transductiv...
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02/03/2021
Adversarially Robust Learning with Unknown Perturbation Sets
We study the problem of learning predictors that are robust to adversari...
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10/22/2020
Reducing Adversarially Robust Learning to Non-Robust PAC Learning
We study the problem of reducing adversarially robust learning to standa...
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07/10/2020
Beyond Perturbations: Learning Guarantees with Arbitrary Adversarial Test Examples
We present a transductive learning algorithm that takes as input trainin...
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05/15/2020
Efficiently Learning Adversarially Robust Halfspaces with Noise
We study the problem of learning adversarially robust halfspaces in the ...
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03/09/2020
Approximate is Good Enough: Probabilistic Variants of Dimensional and Margin Complexity
We present and study approximate notions of dimensional and margin compl...
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02/12/2019
VC Classes are Adversarially Robustly Learnable, but Only Improperly
We study the question of learning an adversarially robust predictor. We ...
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01/22/2017