Present application specific embedded systems tend to choose instruction set extensions (ISEs) based on limitations imposed by the available data bandwidth to custom functional un...
Panagiotis Athanasopoulos, Philip Brisk, Yusuf Leb...
Online Convex Programming (OCP) is a recently developed model of sequential decision-making in the presence of time-varying uncertainty. In this framework, a decisionmaker selects ...
A novel region-based progressive stereo matching algorithm is presented. It combines the strengthes of previous region-based and progressive approaches. The progressive framework ...
For a Markov Decision Process with finite state (size S) and action spaces (size A per state), we propose a new algorithm--Delayed Q-Learning. We prove it is PAC, achieving near o...
Alexander L. Strehl, Lihong Li, Eric Wiewiora, Joh...
Bayesian networks are a powerful probabilistic representation, and their use for classification has received considerable attention. However, they tend to perform poorly when lear...