Titlebook: Integration of Constraint Programming, Artificial Intelligence, and Operations Research; 19th International C Pierre Schaus Conference proc

恶梦

书目名称Integration of Constraint Programming, Artificial Intelligence, and Operations Research影响因子(影响力)




书目名称Integration of Constraint Programming, Artificial Intelligence, and Operations Research影响因子(影响力)学科排名




书目名称Integration of Constraint Programming, Artificial Intelligence, and Operations Research网络公开度




书目名称Integration of Constraint Programming, Artificial Intelligence, and Operations Research网络公开度学科排名




书目名称Integration of Constraint Programming, Artificial Intelligence, and Operations Research被引频次




书目名称Integration of Constraint Programming, Artificial Intelligence, and Operations Research被引频次学科排名




书目名称Integration of Constraint Programming, Artificial Intelligence, and Operations Research年度引用




书目名称Integration of Constraint Programming, Artificial Intelligence, and Operations Research年度引用学科排名




书目名称Integration of Constraint Programming, Artificial Intelligence, and Operations Research读者反馈




书目名称Integration of Constraint Programming, Artificial Intelligence, and Operations Research读者反馈学科排名

Allodynia

0302-9743 ed and selected from a total of 60 submissions. The conference program included a Master Class on the topic "Bridging the Gap between Machine Learning and Optimization”..978-3-031-08010-4978-3-031-08011-1Series ISSN 0302-9743 Series E-ISSN 1611-3349

臆断

恶心

Conference proceedings 2022Operations Research, CPAIOR 2022, which was held in Los Angeles, CA, USA, in June 2022.The 28 regular papers presented were carefully reviewed and selected from a total of 60 submissions. The conference program included a Master Class on the topic "Bridging the Gap between Machine Learning and Optim

myocardium

,Leveraging Integer Linear Programming to Learn Optimal Fair Rule Lists,iciently before proposing an Integer Linear Programming method, leveraging accuracy, sparsity and fairness jointly for better pruning. Our thorough experiments show clear benefits of our approach regarding the exploration of the search space.

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legislate

Stochastic Decision Diagrams,optimal solution. This results in a general and completely novel method for obtaining optimization bounds for stochastic dynamic programming, and the only method that can be applied to the original state space. We report computational experience on stochastic maximum clique (equivalently, maximum independent set) problem instances.

chiropractor

Munificent

,Learning a Propagation Complete Formula, We have implemented both approaches and compared them experimentally. Babka et al. (2013) showed that checking if a CNF formula admits an empowering implicate is an NP-complete problem. We propose a particular CNF encoding which allows us to use a SAT solver to check propagation completeness, or to find an empowering implicate.

craven

,Dealing with the Product Constraint,. We propose and compare different representations allowing to compute the set of solutions of this problem exactly or up to a certain precision. We also give an efficient method to represent that constraint by a Multi-valued Decision Diagram (MDD) in order to combine this constraint with some others MDDs.