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Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
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Instance-Specific Algorithm Configuration (Hardcover, 2014 ed.)
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Instance-Specific Algorithm Configuration (Hardcover, 2014 ed.)
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This book presents a modular and expandable technique in the
rapidly emerging research area of automatic configuration and
selection of the best algorithm for the instance at hand. The
author presents the basic model behind ISAC and then details a
number of modifications and practical applications. In particular,
he addresses automated feature generation, offline algorithm
configuration for portfolio generation, algorithm selection,
adaptive solvers, online tuning, and parallelization. The author's
related thesis was honorably mentioned (runner-up) for the ACP
Dissertation Award in 2014, and this book includes some expanded
sections and notes on recent developments. Additionally, the
techniques described in this book have been successfully applied to
a number of solvers competing in the SAT and MaxSAT International
Competitions, winning a total of 18 gold medals between 2011 and
2014. The book will be of interest to researchers and practitioners
in artificial intelligence, in particular in the area of machine
learning and constraint programming.
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