Instance-specific Algorithm Configuration by Yuri MalitskyInstance-specific Algorithm Configuration by Yuri Malitsky

Instance-specific Algorithm Configuration

byYuri Malitsky

Paperback | August 23, 2016

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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.

Dr. Yuri Malitsky received his PhD from Brown University in 2012 for his work on the Instance-Specific Algorithm Configuration (ISAC) approach. He was a postdoc in the Cork Constraint Computation Centre from 2012 to 2014. He is now a postdoc at the IBM Thomas J. Watson Research Center, working on problems in machine learning, combinato...
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Title:Instance-specific Algorithm ConfigurationFormat:PaperbackDimensions:134 pages, 23.5 × 15.5 × 0.17 inPublished:August 23, 2016Publisher:Springer NatureLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:3319381237

ISBN - 13:9783319381237

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Table of Contents

Introduction.- Survey of Related Work.- Architecture of Instance-Specific Algorithm Configuration Approach.- Applying ISAC to Portfolio Selection.- Generating a Portfolio of Diverse Solvers.- Handling Features.- Developing Adaptive Solvers.- Making Decisions Online.- Conclusions.