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Conference Papers Year : 2010

Building Portfolios for the Protein Structure Prediction Problem

Abstract

This paper, concerned with the protein structure prediction problem, aims at automatically selecting the Constraint Satisfaction algorithm best suited to the problem instance at hand. The contribution is twofold. Firstly, the selection criterion is the quality (minimal cost) in expectation of the solution found after a fixed amount of time, as opposed to the expected runtime. Secondly, the presented approach, based on supervised Machine Learning algorithms, considers the original description of the protein structure problem, as opposed to the features related to the SAT or CSP encoding of the problem.
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Dates and versions

inria-00515138 , version 1 (05-09-2010)

Identifiers

  • HAL Id : inria-00515138 , version 1

Cite

Alejandro Arbelaez, Youssef Hamadi, Michèle Sebag. Building Portfolios for the Protein Structure Prediction Problem. Workshop on Constraint Based Methods for Bioinformatics, Jul 2010, Edinburgh, United Kingdom. ⟨inria-00515138⟩
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