Phase Transitions In Machine Learning
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Phase Transitions In Machine Learning
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Author : Lorenza Saitta
language : en
Publisher: Cambridge University Press
Release Date : 2011-06-16
Phase Transitions In Machine Learning written by Lorenza Saitta and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-06-16 with Computers categories.
Phase transitions typically occur in combinatorial computational problems and have important consequences, especially with the current spread of statistical relational learning as well as sequence learning methodologies. In Phase Transitions in Machine Learning the authors begin by describing in detail this phenomenon, and the extensive experimental investigation that supports its presence. They then turn their attention to the possible implications and explore appropriate methods for tackling them. Weaving together fundamental aspects of computer science, statistical physics and machine learning, the book provides sufficient mathematics and physics background to make the subject intelligible to researchers in AI and other computer science communities. Open research issues are also discussed, suggesting promising directions for future research.
Phase Transitions In Machine Learning
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Author : Lorenza Saitta
language : en
Publisher:
Release Date : 2011
Phase Transitions In Machine Learning written by Lorenza Saitta and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Machine learning categories.
This state-of-the-art overview of the field describes how phase transitions occur and teaches appropriate methods for tackling the consequent problems.
Phase Transitions In Machine Learning
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Author : Lorenza Saitta
language : en
Publisher:
Release Date : 2011
Phase Transitions In Machine Learning written by Lorenza Saitta and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with COMPUTERS / Computer Vision & Pattern Recognition categories.
This state-of-the-art overview of the field describes how phase transitions occur and teaches appropriate methods for tackling the consequent problems.
Phase Transitions In Machine Learning
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Author : Lorenza Saitta
language : en
Publisher:
Release Date : 2011
Phase Transitions In Machine Learning written by Lorenza Saitta and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Machine learning categories.
"Phase transitions typically occur in combinatorial computational problems and have important consequences, especially with the current spread of statistical relational learning and as sequence learning methodologies. In Phase Transitions in Machine Learning the authors begin by describing in detail this phenomenon and the extensive experimental investigation that supports its presence. They then turn their attention to the possible implications and explore appropriate methods for tackling them"--
Quantum Phase Transitions
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Author : Subir Sachdev
language : en
Publisher: Cambridge University Press
Release Date : 2011-04-07
Quantum Phase Transitions written by Subir Sachdev and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-04-07 with Science categories.
Describing the physical properties of quantum materials near critical points with long-range many-body quantum entanglement, this book introduces readers to the basic theory of quantum phases, their phase transitions and their observable properties. This second edition begins with a new section suitable for an introductory course on quantum phase transitions, assuming no prior knowledge of quantum field theory. It also contains several new chapters to cover important recent advances, such as the Fermi gas near unitarity, Dirac fermions, Fermi liquids and their phase transitions, quantum magnetism, and solvable models obtained from string theory. After introducing the basic theory, it moves on to a detailed description of the canonical quantum-critical phase diagram at non-zero temperatures. Finally, a variety of more complex models are explored. This book is ideal for graduate students and researchers in condensed matter physics and particle and string theory.
Applications Of Machine Learning To Studies Of Quantum Phase Transitions
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Author : Laura Malo Roset
language : en
Publisher:
Release Date : 2019
Applications Of Machine Learning To Studies Of Quantum Phase Transitions written by Laura Malo Roset and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.
In the past years Machine Learning has shown to be a useful tool in quantum many-body physics to detect phase transitions. Being able to identify phases via machine learning introduces the question of how did the algorithm learn to classify them, and thus how to interpret the model?s prediction. In this thesis we present a study of the transition from a normal insulator to a topological insulator. We study this quantum phase transition in the framework of the Su-Schrie?er-Heeger model. In the area of Deep Learning, we introduce two models, a normal convolutional neural network and a model based on deep residual learning. In particular, we focus on the interpretability of the model and its prediction by generating class activation maps (CAM) using a global average pooling (GAP) layer. We show the application of this technique by applying it on the model without disorder and with disorder. Here we give further analysis of the detection of states using transfer learning from no disordered to disordered systems. We conclude that the neural network is able to detect edge states when there is no disorder but unable to distinguish between edge states and Anderson localized states when disorder is introduced.
Statistical Mechanics Of Phases And Phase Transitions
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Author : Steven A. Kivelson
language : en
Publisher: Princeton University Press
Release Date : 2024-06-25
Statistical Mechanics Of Phases And Phase Transitions written by Steven A. Kivelson and has been published by Princeton University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-25 with Science categories.
"Statistical mechanics deploys a powerful set of mathematical approaches for studying thermodynamic properties of complex physical systems. This textbook introduces students to the statistical mechanics of systems undergoing changes of state, focusing on the basic principles for classifying distinct thermodynamic phases and the critical phenomena associated with transitions between them. Uniquely designed to promote active learning, Statistical Mechanics of Phases and Phase Transitions presents some of the most beautiful and profound concepts in physics, enabling students to obtain an essential understanding of a computationally challenging subject without getting lost in the details."--Back cover.
Encyclopedia Of Machine Learning
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Author : Claude Sammut
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-03-28
Encyclopedia Of Machine Learning written by Claude Sammut and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-03-28 with Computers categories.
This comprehensive encyclopedia, in A-Z format, provides easy access to relevant information for those seeking entry into any aspect within the broad field of Machine Learning. Most of the entries in this preeminent work include useful literature references.
Machine Learning Ecml 2002
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Author : Tapio Elomaa
language : en
Publisher: Springer
Release Date : 2002-01-01
Machine Learning Ecml 2002 written by Tapio Elomaa and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-01-01 with Computers categories.
This book constitutes the refereed preceedings of the 13th European Conference on Machine Learning, ECML 2002, held in Helsinki, Finland in August 2002. The 41 revised full papers presented together with 4 invited contributions were carefully reviewed and selected from numerous submissions. Among the topics covered are computational discovery, search strategies, Classification, support vector machines, kernel methods, rule induction, linear learning, decision tree learning, boosting, collaborative learning, statistical learning, clustering, instance-based learning, reinforcement learning, multiagent learning, multirelational learning, Markov decision processes, active learning, etc.
Machine Learning And Deep Learning In Efficacy Improvement Of Healthcare Systems
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Author : Om Prakash Jena
language : en
Publisher: CRC Press
Release Date : 2022-05-18
Machine Learning And Deep Learning In Efficacy Improvement Of Healthcare Systems written by Om Prakash Jena and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-18 with Computers categories.
The goal of medical informatics is to improve life expectancy, disease diagnosis and quality of life. Medical devices have revolutionized healthcare and have led to the modern age of machine learning, deep learning and Internet of Medical Things (IoMT) with their proliferation, mobility and agility. This book exposes different dimensions of applications for computational intelligence and explains its use in solving various biomedical and healthcare problems in the real world. This book describes the fundamental concepts of machine learning and deep learning techniques in a healthcare system. The aim of this book is to describe how deep learning methods are used to ensure high-quality data processing, medical image and signal analysis and improved healthcare applications. This book also explores different dimensions of computational intelligence applications and illustrates its use in the solution of assorted real-world biomedical and healthcare problems. Furthermore, it provides the healthcare sector with innovative advances in theory, analytical approaches, numerical simulation, statistical analysis, modelling, advanced deployment, case studies, analytical results, computational structuring and significant progress in the field of machine learning and deep learning in healthcare applications. FEATURES Explores different dimensions of computational intelligence applications and illustrates its use in the solution of assorted real-world biomedical and healthcare problems Provides guidance in developing intelligence-based diagnostic systems, efficient models and cost-effective machines Provides the latest research findings, solutions to the concerning issues and relevant theoretical frameworks in the area of machine learning and deep learning for healthcare systems Describes experiences and findings relating to protocol design, prototyping, experimental evaluation, real testbeds and empirical characterization of security and privacy interoperability issues in healthcare applications Explores and illustrates the current and future impacts of pandemics and mitigates risk in healthcare with advanced analytics This book is intended for students, researchers, professionals and policy makers working in the fields of public health and in the healthcare sector. Scientists and IT specialists will also find this book beneficial for research exposure and new ideas in the field of machine learning and deep learning.