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» Persistence in discrete optimization under data uncertainty
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ECAI
2006
Springer
15 years 1 months ago
Possibilistic Influence Diagrams
Abstract. In this article we present the framework of Possibilistic Influence Diagrams (PID), which allow to model in a compact form problems of sequential decision making under un...
Laurent Garcia, Régis Sabbadin
JMLR
2010
103views more  JMLR 2010»
14 years 4 months ago
Learning Nonlinear Dynamic Models from Non-sequenced Data
Virtually all methods of learning dynamic systems from data start from the same basic assumption: the learning algorithm will be given a sequence of data generated from the dynami...
Tzu-Kuo Huang, Le Song, Jeff Schneider
AIPS
2007
14 years 11 months ago
Learning to Plan Using Harmonic Analysis of Diffusion Models
This paper summarizes research on a new emerging framework for learning to plan using the Markov decision process model (MDP). In this paradigm, two approaches to learning to plan...
Sridhar Mahadevan, Sarah Osentoski, Jeffrey Johns,...
ICIP
2008
IEEE
15 years 11 months ago
Estimation of optimum coding redundancy and frequency domain analysis of attacks for YASS - a randomized block based hiding sche
Our recently introduced JPEG steganographic method called Yet Another Steganographic Scheme (YASS) can resist blind steganalysis by embedding data in the discrete cosine transform...
Anindya Sarkar, Lakshmanan Nataraj, B. S. Manjunat...
JMLR
2006
124views more  JMLR 2006»
14 years 9 months ago
Policy Gradient in Continuous Time
Policy search is a method for approximately solving an optimal control problem by performing a parametric optimization search in a given class of parameterized policies. In order ...
Rémi Munos