We propose a new approach to reinforcement learning which combines least squares function approximation with policy iteration. Our method is model-free and completely off policy. ...
Background: Inference of gene regulatory networks is a key goal in the quest for understanding fundamental cellular processes and revealing underlying relations among genes. With ...
Ioannis A. Maraziotis, Andrei Dragomir, Dimitris T...
Estimating human body poses in static images is important for many image understanding applications including semantic content extraction and image database query and retrieval. Th...
The interval discrimination task is a classical experimental paradigm that is employed to study working memory and decision making and typically involves four phases. First, the s...
We present an adaptive framework for condensation algorithms in the context of human-face tracking. We attack the face tracking problem by making factored sampling more efficient a...
Yui Man Lui, J. Ross Beveridge, L. Darrell Whitley