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Hypothesis Set Stability and Generalization
Our main result is a generalization bound for data-dependent hypothesis sets expressed in terms of a notion of hypothesis set stability and a notion of Rademacher complexity for data-dependent hypothesis sets that we introduce.
Relative Deviation Learning Bounds and Generalization with Unbounded Loss Functions
We present an extensive analysis of relative deviation bounds, including detailed proofs of two-sided inequalities and their implications.
Tight Lower Bound on the Probability of a Binomial Exceeding its Expectation
We give the proof of a tight lower bound on the probability that a binomial random variable exceeds its expected value.
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