TY - BOOK AU - Gori,Marco AU - AU - Betti,Alessandro AU - Melacci,Stefano AU - Gori,Marco AU - AU - AU - TI - Machine learning: a constraint-based approach SN - 9780323984690 U1 - 006.31 23 PY - 2024/// PB - Cambridge Morgan Kaufmann KW - Machine learning KW - Algorithms N1 - Previous edition: published as by Marco Gori. 2018;

1. The Big Picture 2. Learning Principles 3. Linear-Threshold Machines 4. Kernel Machines 5. Deep Architectures 6. Learning from Constraints 7. Epilogue 8. Answers to selected exercises

; Includes bibliographical references and index N2 - Machine Learning: A Constraint-Based Approach, Second Edition provides readers with a refreshing look at the basic models and algorithms of machine learning, with an emphasis on current topics of interest that include neural networks and kernel machines. The book presents the information in a truly unified manner that is based on the notion of learning from environmental constraints. It draws a path towards deep integration with machine learning that relies on the idea of adopting multivalued logic formalisms, such as in fuzzy systems. Special attention is given to deep learning, which nicely fits the constrained-based approach followed in this book. The book presents a simpler unified notion of regularization, which is strictly connected with the parsimony principle, including 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 UR - https://ezproxy.lib.gla.ac.uk/login?url=https://www.sciencedirect.com/science/book/9780323898591 ER -