Machine Learning
Morgan Kaufmann (Verlag)
978-0-08-100659-7 (ISBN)
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The book presents the information in a truly unified manner that is based on the notion of learning from environmental constraints. While regarding symbolic knowledge bases as a collection of constraints, the book draws a path towards a deep integration with machine learning that relies on the idea of adopting multivalued logic formalisms, like in fuzzy systems. A special attention is reserved to deep learning, which nicely fits the constrained- based approach followed in this book.
This book presents a simpler unified notion of regularization, which is strictly connected with the parsimony principle, and includes many solved exercises that are classified according to the Donald Knuth ranking of difficulty, which essentially consists of a mix of warm-up exercises that lead to deeper research problems. A software simulator is also included.
Professor Gori's research interests are in the field of artificial intelligence, with emphasis on machine learning and game playing. He is a co-author of the book “Web Dragons: Inside the myths of search engines technologies, Morgan Kauffman (Elsevier), 2007. He was the Chairman of the Italian Chapter of the IEEE Computational Intelligence Society, and the President of the Italian Association for Artificial Intelligence. He is in the list of top Italian scientists kept by VIAAcademy(http://www.topitalianscientists.org/top_italian_scientists.aspx). Dr. Gori is a fellow of the IEEE, ECCAI, and IAPR.
1. The Big Picture2. Learning Principles3. Linear-Threshold Machines4. Kernel Machines5. Deep Architectures6. Learning and Reasoning with Constraints7. Epilogue8. Answers to selected exercises
Appendices:Constrained optimization in Finite DimensionsRegularization operatorsCalculus of variationsIndex to Notations
Erscheinungsdatum | 21.02.2018 |
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Verlagsort | London |
Sprache | englisch |
Maße | 191 x 235 mm |
Gewicht | 810 g |
Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
ISBN-10 | 0-08-100659-4 / 0081006594 |
ISBN-13 | 978-0-08-100659-7 / 9780081006597 |
Zustand | Neuware |
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