Relative deviation learning bounds and generalization with unbounded loss functions - Cortes, Corinna; Greenberg, Spencer; Mohri, Mehryar (Annals of mathematics and artificial intelligence, 2019)
We present an extensive analysis of relative deviation bounds, including detailed proofs of two-sided inequalities and their implications. We also give detailed proofs of two-sided generalization bounds that hold in the general case of unbounded loss functions, under the assumption that a moment of the loss is bounded. We then illustrate how to apply these results in a sample application: the analysis of importance weighting.