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" ALGORITHM SELECTION FOR SORTING AND PROBABILISTIC INFERENCE: A MACHINE LEARNING-BASED APPROACH "


Document Type : Latin Dissertation
Language of Document : English
Record Number : 149636
Doc. No : ET21428
Main Entry : HAIPENG GUO
Title Proper : ALGORITHM SELECTION FOR SORTING AND PROBABILISTIC INFERENCE: A MACHINE LEARNING-BASED APPROACH
Note : This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract : The algorithm selection problem aims at selecting the best algorithm for a givencomputational problem instance according to some characteristics of the instance. Inthis dissertation, we first introduce some results from theoretical investigation of thealgorithm selection problem. We show, by Rice's theorem, the nonexistence of anautomatic algorithm selection program based only on the description of the inputinstance and the competing algorithms. We also describe an abstract theoreticalframework of instance hardness and algorithm performance based on Kolmogorovcomplexity.
Subject : Electericl tess
: برق
electronic file name : TL44589.pdf
Title and statement of responsibility and : ALGORITHM SELECTION FOR SORTING AND PROBABILISTIC INFERENCE: A MACHINE LEARNING-BASED APPROACH [Thesis]
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TL44589.pdf
TL44589.pdf
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