This state-of-the-art overview of the field describes how phase transitions occur and teaches appropriate methods for tackling the consequent problems.
This state-of-the-art overview of the field describes how phase transitions occur and teaches appropriate methods for tackling the consequent problems.
Antoine Cornuéjols is Full Professor of Computer Science at the AgroParisTech Engineering School in Paris.
Inhaltsangabe
Preface Acknowledgements Notation 1. Introduction 2. Statistical physics and phase transitions 3. The satisfiability problem 4. Constraint satisfaction problems 5. Machine learning 6. Searching the hypothesis space 7. Statistical physics and machine learning 8. Learning, SAT, and CSP 9. Phase transition in FOL covering test 10. Phase transitions and relational learning 11. Phase transitions in grammatical inference 12. Phase transitions in complex systems 13. Phase transitions in natural systems 14. Discussions and open issues Appendix A. Phase transitions detected in two real cases Appendix B. An intriguing idea References Index.
Preface Acknowledgements Notation 1. Introduction 2. Statistical physics and phase transitions 3. The satisfiability problem 4. Constraint satisfaction problems 5. Machine learning 6. Searching the hypothesis space 7. Statistical physics and machine learning 8. Learning, SAT, and CSP 9. Phase transition in FOL covering test 10. Phase transitions and relational learning 11. Phase transitions in grammatical inference 12. Phase transitions in complex systems 13. Phase transitions in natural systems 14. Discussions and open issues Appendix A. Phase transitions detected in two real cases Appendix B. An intriguing idea References Index.
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