23 citations · 27 across the 11 of their papers we have counts for
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cs.CG2020
Point Location and Active Learning: Learning Halfspaces Almost Optimally
Max Hopkins, Daniel M. Kane, Shachar Lovett +1
Given a finite set and a binary linear classifier , how many queries of the form are required to learn the label of eve…
cs.LG2020★ 23 cited
Agnostic Q-learning with Function Approximation in Deterministic Systems: Tight Bounds on Approximation Error and Sample Complexity
Simon S. Du, Jason D. Lee, Gaurav Mahajan +1
The current paper studies the problem of agnostic -learning with function approximation in deterministic systems where the optimal -function is approximable by a function in…
cs.LG2020★ 3 cited
Noise-tolerant, Reliable Active Classification with Comparison Queries
Max Hopkins, Daniel Kane, Shachar Lovett +1
With the explosion of massive, widely available unlabeled data in the past years, finding label and time efficient, robust learning algorithms has become ever more important in the…