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ATAL
2008
Springer
14 years 11 months ago
Searching for approximate equilibria in empirical games
When exploring a game over a large strategy space, it may not be feasible or cost-effective to evaluate the payoff of every relevant strategy profile. For example, determining a p...
Patrick R. Jordan, Yevgeniy Vorobeychik, Michael P...
IJCAI
2007
14 years 11 months ago
Relevance Estimation and Value Calibration of Evolutionary Algorithm Parameters
— Calibrating the parameters of an evolutionary algorithm (EA) is a laborious task. The highly stochastic nature of an EA typically leads to a high variance of the measurements. ...
Volker Nannen, A. E. Eiben
NIPS
2007
14 years 11 months ago
Anytime Induction of Cost-sensitive Trees
Machine learning techniques are increasingly being used to produce a wide-range of classifiers for complex real-world applications that involve nonuniform testing costs and miscl...
Saher Esmeir, Shaul Markovitch
72
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AAAI
2006
14 years 11 months ago
When a Decision Tree Learner Has Plenty of Time
The majority of the existing algorithms for learning decision trees are greedy--a tree is induced top-down, making locally optimal decisions at each node. In most cases, however, ...
Saher Esmeir, Shaul Markovitch
AIPS
2004
14 years 11 months ago
Task Swapping for Schedule Improvement: A Broader Analysis
In this paper we analyze and extend a recently developed "task-swapping procedure" for improving schedules in oversubscribed situations. In such situations, there are ta...
Laurence A. Kramer, Stephen F. Smith