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The Revision of the Cambridge Business English Certificates
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First International Workshop, TAILOR 2020, Virtual Event, September 4–5, 2020, Revised Selected Papers
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This book constitutes the thoroughly refereed conference proceedings of the First International Workshop on the Foundation of Trustworthy AI - Integrating Learning, Optimization and Reasoning, TAILOR 2020, held virtually in September 2020, associated with ECAI 2020, the 24th European Conference on Artificial Intelligence.
The 11 revised full papers presented together with 6 short papers and 6 position papers were reviewed and selected from 52 submissions. The contributions address various issues for Trustworthiness, Learning, reasoning, and optimization, Deciding and Learning How to Act, AutoAI, and Reasoning and Learning in Social Contexts.20th International Conference, CP 2014, Lyon, France, September 8-12, 2014, Proceedings
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Foundations of a Cross-Disciplinary Approach
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A successful integration of constraint programming and data mining has the potential to lead to a new ICT paradigm with far reaching implications. It could change the face of data mining and machine learning, as well as constraint programming technology. 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.
This book reports on some key results obtained on this integrated and cross- disciplinary approach within the European FP7 FET Open project no. 284715 on “Inductive Constraint Programming” and a number of associated workshops and Dagstuhl seminars. The book is structured in five parts: background; learning to model; learning to solve; constraint programming for data mining; and showcases.
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