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ICMLA
2009
14 years 11 months ago
Automatic Feature Selection for Model-Based Reinforcement Learning in Factored MDPs
Abstract--Feature selection is an important challenge in machine learning. Unfortunately, most methods for automating feature selection are designed for supervised learning tasks a...
Mark Kroon, Shimon Whiteson
ICASSP
2011
IEEE
14 years 5 months ago
Reinforcement learning for energy-efficient wireless transmission
We consider the problem of energy-efficient point-to-point transmission of delay-sensitive data (e.g. multimedia data) over a fading channel. We propose a rigorous and unified fra...
Nicholas Mastronarde, Mihaela van der Schaar
NIPS
2004
15 years 3 months ago
Approximately Efficient Online Mechanism Design
Online mechanism design (OMD) addresses the problem of sequential decision making in a stochastic environment with multiple self-interested agents. The goal in OMD is to make valu...
David C. Parkes, Satinder P. Singh, Dimah Yanovsky
ICAI
2009
14 years 11 months ago
The Utility of Affect in the Selection of Actions and Goals Under Real-World Constraints
We present a novel affective goal selection mechanism for decision-making in agents with limited computational resources (e.g., such as robots operating under real-time constraint...
Paul W. Schermerhorn, Matthias Scheutz
ECCV
2008
Springer
16 years 3 months ago
A Probabilistic Approach to Integrating Multiple Cues in Visual Tracking
Abstract. This paper presents a novel probabilistic approach to integrating multiple cues in visual tracking. We perform tracking in different cues by interacting processes. Each p...
Wei Du, Justus H. Piater