15 citations · 99 across the 45 of their papers we have counts for
4 papers · 2 filters
Statistically Near-Optimal Hypothesis Selection
Olivier Bousquet, Mark Braverman, Klim Efremenko +2
Hypothesis Selection is a fundamental distribution learning problem where given a comparator-class of distributions, and a sampling access to an unknown tar…
A Theory of PAC Learnability of Partial Concept Classes
Noga Alon, Steve Hanneke, Ron Holzman +1
We extend the theory of PAC learning in a way which allows to model a rich variety of learning tasks where the data satisfy special properties that ease the learning process. For e…
Online Learning with Simple Predictors and a Combinatorial Characterization of Minimax in 0/1 Games
Steve Hanneke, Roi Livni, Shay Moran
Which classes can be learned properly in the online model? -- that is, by an algorithm that at each round uses a predictor from the concept class. While there are simple and natura…
Adversarial Laws of Large Numbers and Optimal Regret in Online Classification
Noga Alon, Omri Ben-Eliezer, Yuval Dagan +3
Laws of large numbers guarantee that given a large enough sample from some population, the measure of any fixed sub-population is well-estimated by its frequency in the sample. We…