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ECAI
2006
Springer
14 years 12 days 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
KDD
2006
ACM
272views Data Mining» more  KDD 2006»
14 years 9 months ago
YALE: rapid prototyping for complex data mining tasks
KDD is a complex and demanding task. While a large number of methods has been established for numerous problems, many challenges remain to be solved. New tasks emerge requiring th...
Ingo Mierswa, Michael Wurst, Ralf Klinkenberg, Mar...
ATAL
2004
Springer
14 years 2 months ago
Approximate Solutions for Partially Observable Stochastic Games with Common Payoffs
Partially observable decentralized decision making in robot teams is fundamentally different from decision making in fully observable problems. Team members cannot simply apply si...
Rosemary Emery-Montemerlo, Geoffrey J. Gordon, Jef...
SODA
2010
ACM
235views Algorithms» more  SODA 2010»
14 years 6 months ago
Algorithmic Lower Bounds for Problems Parameterized by Clique-width
Many NP-hard problems can be solved efficiently when the input is restricted to graphs of bounded tree-width or clique-width. In particular, by the celebrated result of Courcelle,...
Fedor V. Fomin, Petr A. Golovach, Daniel Lokshtano...
AAAI
2008
13 years 11 months ago
Learning and Inference with Constraints
Probabilistic modeling has been a dominant approach in Machine Learning research. As the field evolves, the problems of interest become increasingly challenging and complex. Makin...
Ming-Wei Chang, Lev-Arie Ratinov, Nicholas Rizzolo...