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» Evaluating learning algorithms and classifiers
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IJCAI
2007
15 years 5 months ago
Heuristic Selection of Actions in Multiagent Reinforcement Learning
This work presents a new algorithm, called Heuristically Accelerated Minimax-Q (HAMMQ), that allows the use of heuristics to speed up the wellknown Multiagent Reinforcement Learni...
Reinaldo A. C. Bianchi, Carlos H. C. Ribeiro, Anna...
AAAI
2008
15 years 6 months ago
Bounding the False Discovery Rate in Local Bayesian Network Learning
Modern Bayesian Network learning algorithms are timeefficient, scalable and produce high-quality models; these algorithms feature prominently in decision support model development...
Ioannis Tsamardinos, Laura E. Brown
ECML
2006
Springer
15 years 7 months ago
Why Is Rule Learning Optimistic and How to Correct It
Abstract. In their search through a huge space of possible hypotheses, rule induction algorithms compare estimations of qualities of a large number of rules to find the one that ap...
Martin Mozina, Janez Demsar, Jure Zabkar, Ivan Bra...
SSDBM
2008
IEEE
114views Database» more  SSDBM 2008»
15 years 10 months ago
A General Framework for Increasing the Robustness of PCA-Based Correlation Clustering Algorithms
Abstract. Most correlation clustering algorithms rely on principal component analysis (PCA) as a correlation analysis tool. The correlation of each cluster is learned by applying P...
Hans-Peter Kriegel, Peer Kröger, Erich Schube...
INFOVIS
2000
IEEE
15 years 8 months ago
Interactive Problem Solving via Algorithm Visualization
COMIND is a tool for conceptual design of industrial products. It helps designers define and evaluate the initial design space by using search algorithms to generate sets of feasi...
Pearl Pu, Denis Lalanne