We address the problem of visual category recognition by learning an image-to-image distance function that attempts to satisfy the following property: the distance between images ...
Andrea Frome, Yoram Singer, Fei Sha, Jitendra Mali...
Abstract. We propose a novel active learning strategy based on the compression framework of [9] for label ranking functions which, given an input instance, predict a total order ov...
Reinforcement learning problems are commonly tackled with temporal difference methods, which attempt to estimate the agent's optimal value function. In most real-world proble...
We study the learnability of Threshold functions with bounded weights using membership queries only. We show that the class Ct of Threshold functions with positive integer weights...
Elias Abboud, Nader Agha, Nader H. Bshouty, Nizar ...
We address two open theoretical questions in Policy Gradient Reinforcement Learning. The first concerns the efficacy of using function approximation to represent the state action ...