Principles and Practice of Constraint Programming, Rueher
Автор: Ian P. Gent Название: Principles and Practice of Constraint Programming - CP 2009 ISBN: 3642042430 ISBN-13(EAN): 9783642042430 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume contains the papers presented at CP 2009: The 15th International Conference on Principles and Practice of Constraint Programming. Papers submitted as long papers were accepted at full length or not at all. It is important to note that papers submitted as short papers were held to the same high standards of qualityas long papers.
Автор: Peter J. Stuckey Название: Principles and Practice of Constraint Programming ISBN: 3540859578 ISBN-13(EAN): 9783540859574 Издательство: Springer Рейтинг: Цена: 16070.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Constitutes the refereed proceedings of the 14th International Conference on Principles and Practice of Constraint Programming, CP 2008, Sydney, Australia, September, 2008. This title addresses the issues of computing with constraints ranging from methodological and foundational aspects - using algorithms, environments, languages and models.
Описание: Constitutes the refereed proceedings of the 7th International Conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems, CPAIOR 2010, held in Bologna, Italy, in June 2010.
Описание: Constitutes the refereed proceedings of the 6th International Conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems, CPAIOR 2009, held in Pittsburgh, PA, USA, in May 2009.
Автор: Bessiere Название: Data Mining and Constraint Programming ISBN: 3319501364 ISBN-13(EAN): 9783319501369 Издательство: Springer Рейтинг: Цена: 8106.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: It would not only allow one to use data mining techniques in constraint programming to identify and update constraints and optimization criteria, but also to employ constraints and criteria in data mining and machine learning in order to discover models compatible with prior knowledge.
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