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Robust Empirical Risk Minimization with Tolerance
Developing simple, sample-efficient learning algorithms for robust classification is a pressing issue in today's tech-dominated world, and current theoretical techniques requiring exponential sample complexity and complicated improper learning rules fall far from answering the need.
Active Learning Polynomial Threshold Functions
We initiate the study of active learning polynomial threshold functions (PTFs).
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