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AAAI
2006
14 years 11 months ago
Action Selection in Bayesian Reinforcement Learning
My research attempts to address on-line action selection in reinforcement learning from a Bayesian perspective. The idea is to develop more effective action selection techniques b...
Tao Wang
AAAI
2010
14 years 11 months ago
Active Inference for Collective Classification
Labeling nodes in a network is an important problem that has seen a growing interest. A number of methods that exploit both local and relational information have been developed fo...
Mustafa Bilgic, Lise Getoor
RAS
2010
117views more  RAS 2010»
14 years 7 months ago
Extending BDI plan selection to incorporate learning from experience
An important drawback to the popular Belief, Desire, and Intentions (BDI) paradigm is that such systems include no element of learning from experience. We describe a novel BDI exe...
Dhirendra Singh, Sebastian Sardiña, Lin Pad...
BMCBI
2008
134views more  BMCBI 2008»
14 years 9 months ago
Identification of transcription factor contexts in literature using machine learning approaches
Background: Availability of information about transcription factors (TFs) is crucial for genome biology, as TFs play a central role in the regulation of gene expression. While man...
Hui Yang, Goran Nenadic, John A. Keane
IBPRIA
2009
Springer
15 years 2 months ago
Inference and Learning for Active Sensing, Experimental Design and Control
In this paper we argue that maximum expected utility is a suitable framework for modeling a broad range of decision problems arising in pattern recognition and related fields. Exa...
Hendrik Kück, Matthew Hoffman, Arnaud Doucet,...