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ICML
2010
IEEE
13 years 8 months ago
Feature Selection Using Regularization in Approximate Linear Programs for Markov Decision Processes
Approximate dynamic programming has been used successfully in a large variety of domains, but it relies on a small set of provided approximation features to calculate solutions re...
Marek Petrik, Gavin Taylor, Ronald Parr, Shlomo Zi...
ATVA
2007
Springer
115views Hardware» more  ATVA 2007»
14 years 1 months ago
A Compositional Semantics for Dynamic Fault Trees in Terms of Interactive Markov Chains
Abstract. Dynamic fault trees (DFTs) are a versatile and common formalism to model and analyze the reliability of computer-based systems. This paper presents a formal semantics of ...
Hichem Boudali, Pepijn Crouzen, Mariëlle Stoe...
TSD
2010
Springer
13 years 5 months ago
Comparison of Different Lemmatization Approaches through the Means of Information Retrieval Performance
This paper presents a quantitative performance analysis of two different approaches to the lemmatization of the Czech text data. The first one is based on manually prepared diction...
Jakub Kanis, Lucie Skorkovská
GECCO
2006
Springer
186views Optimization» more  GECCO 2006»
13 years 11 months ago
Genetic algorithms for action set selection across domains: a demonstration
Action set selection in Markov Decision Processes (MDPs) is an area of research that has received little attention. On the other hand, the set of actions available to an MDP agent...
Greg Lee, Vadim Bulitko
CIKM
2005
Springer
14 years 1 months ago
A hybrid approach to NER by MEMM and manual rules
This paper describes a framework for defining domain specific Feature Functions in a user friendly form to be used in a Maximum Entropy Markov Model (MEMM) for the Named Entity Re...
Moshe Fresko, Binyamin Rosenfeld, Ronen Feldman