Classifier-based constraint acquisition

DOI10.1007/s10472-021-09736-4OpenAlexW3156488694MaRDI QIDQ2043441

Yanyan Li

Publication date: 2 August 2021

Published in: Annals of Mathematics and Artificial Intelligence (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10472-021-09736-4

zbMATH Keywords

Boolean satisfiabilityconstraint acquisitionNaive Bayes classifier

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05) Computational aspects of satisfiability (68R07)

Related Items (1)

Learning constraints through partial queries

Cites Work

• Unnamed Item
• Constraint acquisition
• Empirical decision model learning
• Auction optimization using regression trees and linear models as integer programs
• Clausal discovery
• Constraint models for the covering test problem
• Increasing constraint propagation by redundant modeling: An experience report
• First-order \(jk\)-clausal theories are PAC-learnable
• On the optimality of the simple Bayesian classifier under zero-one loss
• Progress towards the Holy Grail
• Deep neural networks and mixed integer linear optimization
• Time-bounded query generator for constraint acquisition
• Automatic synthesis of constraints from examples using mixed integer linear programming
• Introduction to Information Retrieval
• A theory of the learnable
• Turing’s anticipation of empirical bayes in connection with the cryptanalysis of the naval enigma^*
• Bayes Factors
• Embedding Decision Trees and Random Forests in Constraint Programming
• Principles and Practice of Constraint Programming – CP 2004

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