This book explains the main ideas behind MemComputing, its theoretical foundations and its applicability to a wide variety of combinatorial optimization problems, machine learning, and quantum mechanics.
This book explains the main ideas behind MemComputing, its theoretical foundations and its applicability to a wide variety of combinatorial optimization problems, machine learning, and quantum mechanics.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Massimiliano Di Ventra obtained his undergraduate degree in Physics summa cum laude from the University of Trieste (Italy) in 1991 and did his PhD studies at the Swiss Federal Institute of Technology in Lausanne 1993-1997. He is now professor of Physics at the University of California, San Diego. Di Ventra's research interests are in condensed-matter theory and unconventional computing. He has been invited to deliver more than 300 talks worldwide on these topics. He has published more than 200 papers in refereed journals and 3 textbooks, and has 4 granted patents. He is a fellow of the American Physical Society and the Institute of Physics, and a foreign member of Academia Europaea. In 2018 he was named Highly Cited Researcher by Clarivate Analytics and he is the recipient of the 2020 Feynman Prize for Theory in Nanotechnology.
Inhaltsangabe
Preface 1: The physics of computing and computing with physics 2: Computing: The Turing way 3: Dynamical systems picture of computing 4: Memory, memelements, active elements, and memprocessors 5: Universal MemComputing machine 6: Digital MemComputing machines 7: Self-organizing gates and circuits 8: Numerical simulations of DMMs 9: Application to combinatorial optimization problems 10: Application to machine learning and quantum mechanics 11: Topological features of DMMs 12: Approach to equilibrium and the ordered state of DMMs 13: Epilogue and future work
Preface 1: The physics of computing and computing with physics 2: Computing: The Turing way 3: Dynamical systems picture of computing 4: Memory, memelements, active elements, and memprocessors 5: Universal MemComputing machine 6: Digital MemComputing machines 7: Self-organizing gates and circuits 8: Numerical simulations of DMMs 9: Application to combinatorial optimization problems 10: Application to machine learning and quantum mechanics 11: Topological features of DMMs 12: Approach to equilibrium and the ordered state of DMMs 13: Epilogue and future work
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