Statistical generalization: theory and applications
نویسندگان
چکیده
Benjamin W. Wah, A. Ieumwananonthachai, Shu Yao, and Ting Yu Center for Reliable and High Performance Computing Coordinated Science Laboratory University of Illinois, Urbana-Champaign 1308 West Main Street, Urbana, IL 61801, USA fwah, arthuri, yshu, [email protected] Abstract In this paper, we discuss a new approach to generalize heuristic methods (HMs) to new test cases of an application, and conditions under which such generalization is possible. Generalization is di cult when performance values of HMs are characterized by multiple statistical distributions across subsets of test cases of an application. We de ne a new measure called probability of win and propose three methods to evaluate it: interval analysis, maximum likelihood estimate, and Bayesian analysis. We show experimental results on new HMs found for blind equalization and branchand-bound search.
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