Consider the following problem: given sets of unlabeled observations, each set with known label proportions, predict the labels of another set of observations, also with known lab...
Alex J. Smola, Novi Quadrianto, Quoc V. Le, Tib&ea...
Properties of ensemble classification can be studied using the framework of Monte Carlo stochastic algorithms. Within this framework it is also possible to define a new ensemble c...
We consider incorporating action elimination procedures in reinforcement learning algorithms. We suggest a framework that is based on learning an upper and a lower estimates of th...
Abstract. We give a lower bound for the error of any unitarily invariant algorithm learning half-spaces against the uniform or related distributions on the unit sphere. The bound i...
Empirical evidence suggests that hashing is an effective strategy for dimensionality reduction and practical nonparametric estimation. In this paper we provide exponential tail bo...
Kilian Q. Weinberger, Anirban Dasgupta, John Langf...