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ECML
2005
Springer
15 years 10 months ago
Active Learning in Partially Observable Markov Decision Processes
This paper examines the problem of finding an optimal policy for a Partially Observable Markov Decision Process (POMDP) when the model is not known or is only poorly specified. W...
Robin Jaulmes, Joelle Pineau, Doina Precup
SIP
2007
15 years 5 months ago
A variational segmentation framework using active contours and thresholding
Segmentation involves separating distinct regions in an image. In this note, we present a novel variational approach to perform this task. We propose an energy functional that nat...
Samuel Dambreville, Marc Niethammer, Anthony J. Ye...
CORR
2010
Springer
146views Education» more  CORR 2010»
15 years 4 months ago
Adaptive Submodularity: A New Approach to Active Learning and Stochastic Optimization
Solving stochastic optimization problems under partial observability, where one needs to adaptively make decisions with uncertain outcomes, is a fundamental but notoriously diffic...
Daniel Golovin, Andreas Krause
CGF
2000
117views more  CGF 2000»
15 years 4 months ago
Versatile Tuning of Humanoid Agent Activity
In this paper, we present an integration framework for heterogeneous motion generators. The objective is to outline issues that are currently easily solved in professional post-pr...
Luc Emering, Ronan Boulic, Tom Molet, Daniel Thalm...
SIGSOFT
2003
ACM
16 years 5 months ago
Protecting C programs from attacks via invalid pointer dereferences
Writes via unchecked pointer dereferences rank high among vulnerabilities most often exploited by malicious code. The most common attacks use an unchecked string copy to cause a b...
Suan Hsi Yong, Susan Horwitz