The importance of learning distance functions is gradually being acknowledged by the machine learning community, and different techniques are suggested that can successfully learn ...
Abstract. In contrast to the standard inductive inference setting of predictive machine learning, in real world learning problems often the test instances are already available at ...
Although TD-Gammon is one of the major successes in machine learning, it has not led to similar impressive breakthroughs in temporal difference learning for other applications or ...
Most reinforcement learning models of animal conditioning operate under the convenient, though fictive, assumption that Pavlovian conditioning concerns prediction learning whereas...
Peter Dayan, Yael Niv, Ben Seymour, Nathaniel D. D...
In this paper we propose and evaluate an algorithm that learns a similarity measure for comparing never seen objects. The measure is learned from pairs of training images labeled ...