Image retrieval critically relies on the distance function used to compare a query image to images in the database. We suggest to learn such distance functions by training binary ...
Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
We consider a model of learning Boolean functions from examples generated by a uniform random walk on {0, 1}n . We give a polynomial time algorithm for learning decision trees and...
Nader H. Bshouty, Elchanan Mossel, Ryan O'Donnell,...
Inducing a classification function from a set of examples in the form of labeled instances is a standard problem in supervised machine learning. In this paper, we are concerned w...
A classical learning problem in Inductive Inference consists of identifying each function of a given class of recursive functions from a finite number of its output values. Unifor...