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cs.LG2025★ 3 cited
The Optimal Approximation Factor in Density Estimation
Olivier Bousquet, Daniel Kane, Shay Moran
Consider the following problem: given two arbitrary densities and a sample-access to an unknown target density , find which of the 's is closer to in total va…
cs.LG2025
Do PAC-Learners Learn the Marginal Distribution?
Max Hopkins, Daniel M. Kane, Shachar Lovett +1
The Fundamental Theorem of PAC Learning asserts that learnability of a concept class is equivalent to the of empirical error in to its mean,…
cs.LG2024
Realizable Learning is All You Need
Max Hopkins, Daniel M. Kane, Shachar Lovett +1
The equivalence of realizable and agnostic learnability is a fundamental phenomenon in learning theory. With variants ranging from classical settings like PAC learning and regressi…