Advanced Mean Field Methods

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Publisher : MIT Press
ISBN 13 : 9780262150545
Total Pages : 300 pages
Book Rating : 4.1/5 (55 download)

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Book Synopsis Advanced Mean Field Methods by : Manfred Opper

Download or read book Advanced Mean Field Methods written by Manfred Opper and published by MIT Press. This book was released on 2001 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the theoretical foundations of advanced mean field methods, explores the relation between the different approaches, examines the quality of the approximation obtained, and demonstrates their application to various areas of probabilistic modeling. A major problem in modern probabilistic modeling is the huge computational complexity involved in typical calculations with multivariate probability distributions when the number of random variables is large. Because exact computations are infeasible in such cases and Monte Carlo sampling techniques may reach their limits, there is a need for methods that allow for efficient approximate computations. One of the simplest approximations is based on the mean field method, which has a long history in statistical physics. The method is widely used, particularly in the growing field of graphical models. Researchers from disciplines such as statistical physics, computer science, and mathematical statistics are studying ways to improve this and related methods and are exploring novel application areas. Leading approaches include the variational approach, which goes beyond factorizable distributions to achieve systematic improvements; the TAP (Thouless-Anderson-Palmer) approach, which incorporates correlations by including effective reaction terms in the mean field theory; and the more general methods of graphical models. Bringing together ideas and techniques from these diverse disciplines, this book covers the theoretical foundations of advanced mean field methods, explores the relation between the different approaches, examines the quality of the approximation obtained, and demonstrates their application to various areas of probabilistic modeling.

Phase-Field Methods in Materials Science and Engineering

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Publisher : John Wiley & Sons
ISBN 13 : 3527632379
Total Pages : 323 pages
Book Rating : 4.5/5 (276 download)

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Book Synopsis Phase-Field Methods in Materials Science and Engineering by : Nikolas Provatas

Download or read book Phase-Field Methods in Materials Science and Engineering written by Nikolas Provatas and published by John Wiley & Sons. This book was released on 2011-07-26 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive and self-contained, one-stop source discusses phase-field methodology in a fundamental way, explaining advanced numerical techniques for solving phase-field and related continuum-field models. It also presents numerical techniques used to simulate various phenomena in a detailed, step-by-step way, such that readers can carry out their own code developments. Features many examples of how the methods explained can be used in materials science and engineering applications.

Sublinear Computation Paradigm

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Publisher : Springer Nature
ISBN 13 : 9811640955
Total Pages : 403 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Sublinear Computation Paradigm by : Naoki Katoh

Download or read book Sublinear Computation Paradigm written by Naoki Katoh and published by Springer Nature. This book was released on 2021-10-19 with total page 403 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book gives an overview of cutting-edge work on a new paradigm called the “sublinear computation paradigm,” which was proposed in the large multiyear academic research project “Foundations of Innovative Algorithms for Big Data.” That project ran from October 2014 to March 2020, in Japan. To handle the unprecedented explosion of big data sets in research, industry, and other areas of society, there is an urgent need to develop novel methods and approaches for big data analysis. To meet this need, innovative changes in algorithm theory for big data are being pursued. For example, polynomial-time algorithms have thus far been regarded as “fast,” but if a quadratic-time algorithm is applied to a petabyte-scale or larger big data set, problems are encountered in terms of computational resources or running time. To deal with this critical computational and algorithmic bottleneck, linear, sublinear, and constant time algorithms are required. The sublinear computation paradigm is proposed here in order to support innovation in the big data era. A foundation of innovative algorithms has been created by developing computational procedures, data structures, and modelling techniques for big data. The project is organized into three teams that focus on sublinear algorithms, sublinear data structures, and sublinear modelling. The work has provided high-level academic research results of strong computational and algorithmic interest, which are presented in this book. The book consists of five parts: Part I, which consists of a single chapter on the concept of the sublinear computation paradigm; Parts II, III, and IV review results on sublinear algorithms, sublinear data structures, and sublinear modelling, respectively; Part V presents application results. The information presented here will inspire the researchers who work in the field of modern algorithms.

The Variational Bayes Method in Signal Processing

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Publisher : Springer Science & Business Media
ISBN 13 : 3540288201
Total Pages : 241 pages
Book Rating : 4.5/5 (42 download)

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Book Synopsis The Variational Bayes Method in Signal Processing by : Václav Šmídl

Download or read book The Variational Bayes Method in Signal Processing written by Václav Šmídl and published by Springer Science & Business Media. This book was released on 2006-03-30 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: Treating VB approximation in signal processing, this monograph is for academic and industrial research groups in signal processing, data analysis, machine learning and identification. It reviews distributional approximation, showing that tractable algorithms for parametric model identification can be generated in off-line and on-line contexts.

Proceedings of the Third SIAM International Conference on Data Mining

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Publisher : SIAM
ISBN 13 : 9780898715453
Total Pages : 368 pages
Book Rating : 4.7/5 (154 download)

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Book Synopsis Proceedings of the Third SIAM International Conference on Data Mining by : Daniel Barbara

Download or read book Proceedings of the Third SIAM International Conference on Data Mining written by Daniel Barbara and published by SIAM. This book was released on 2003-01-01 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: The third SIAM International Conference on Data Mining provided an open forum for the presentation, discussion and development of innovative algorithms, software and theories for data mining applications and data intensive computation. This volume includes 21 research papers.

Text Mining

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Publisher : CRC Press
ISBN 13 : 1420059459
Total Pages : 330 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Text Mining by : Ashok N. Srivastava

Download or read book Text Mining written by Ashok N. Srivastava and published by CRC Press. This book was released on 2009-06-15 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Definitive Resource on Text Mining Theory and Applications from Foremost Researchers in the FieldGiving a broad perspective of the field from numerous vantage points, Text Mining: Classification, Clustering, and Applications focuses on statistical methods for text mining and analysis. It examines methods to automatically cluster and classify te

Probabilistic Models of the Brain

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Publisher : MIT Press
ISBN 13 : 9780262264327
Total Pages : 348 pages
Book Rating : 4.2/5 (643 download)

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Book Synopsis Probabilistic Models of the Brain by : Rajesh P.N. Rao

Download or read book Probabilistic Models of the Brain written by Rajesh P.N. Rao and published by MIT Press. This book was released on 2002-03-29 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: A survey of probabilistic approaches to modeling and understanding brain function. Neurophysiological, neuroanatomical, and brain imaging studies have helped to shed light on how the brain transforms raw sensory information into a form that is useful for goal-directed behavior. A fundamental question that is seldom addressed by these studies, however, is why the brain uses the types of representations it does and what evolutionary advantage, if any, these representations confer. It is difficult to address such questions directly via animal experiments. A promising alternative is to use probabilistic principles such as maximum likelihood and Bayesian inference to derive models of brain function. This book surveys some of the current probabilistic approaches to modeling and understanding brain function. Although most of the examples focus on vision, many of the models and techniques are applicable to other modalities as well. The book presents top-down computational models as well as bottom-up neurally motivated models of brain function. The topics covered include Bayesian and information-theoretic models of perception, probabilistic theories of neural coding and spike timing, computational models of lateral and cortico-cortical feedback connections, and the development of receptive field properties from natural signals.

Energy Minimization Methods in Computer Vision and Pattern Recognition

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Publisher : Springer
ISBN 13 : 3540447458
Total Pages : 652 pages
Book Rating : 4.5/5 (44 download)

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Book Synopsis Energy Minimization Methods in Computer Vision and Pattern Recognition by : Mario Figueiredo

Download or read book Energy Minimization Methods in Computer Vision and Pattern Recognition written by Mario Figueiredo and published by Springer. This book was released on 2003-06-30 with total page 652 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume consists of the 42 papers presented at the International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR2001),whichwasheldatINRIA(InstitutNationaldeRechercheen Informatique et en Automatique) in Sophia Antipolis, France, from September 3 through September 5, 2001. This workshop is the third of a series, which was started with EMMCVPR’97, held in Venice in May 1997, and continued with EMMCVR’99, which took place in York, in July 1999. Minimization problems and optimization methods permeate computer vision (CV), pattern recognition (PR), and many other ?elds of machine intelligence. The aim of the EMMCVPR workshops is to bring together people with research interests in this interdisciplinary topic. Although the subject is traditionally well represented at major international conferences on CV and PR, the EMMCVPR workshops provide a forum where researchers can report their recent work and engage in more informal discussions. We received 70 submissions from 23 countries, which were reviewed by the members of the program committee. Based on the reviews, 24 papers were - cepted for oral presentation and 18 for poster presentation. In this volume, no distinction is made between papers that were presented orally or as posters. The book is organized into ?ve sections, whose topics coincide with the ?ve s- sionsoftheworkshop:“ProbabilisticModelsandEstimation”,“ImageModelling and Synthesis”, “Clustering, Grouping, and Segmentation”, “Optimization and Graphs”, and “Shapes, Curves, Surfaces, and Templates”.

Advances in Neural Information Processing Systems 16

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Publisher : MIT Press
ISBN 13 : 9780262201520
Total Pages : 1694 pages
Book Rating : 4.2/5 (15 download)

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Book Synopsis Advances in Neural Information Processing Systems 16 by : Sebastian Thrun

Download or read book Advances in Neural Information Processing Systems 16 written by Sebastian Thrun and published by MIT Press. This book was released on 2004 with total page 1694 pages. Available in PDF, EPUB and Kindle. Book excerpt: Papers presented at the 2003 Neural Information Processing Conference by leading physicists, neuroscientists, mathematicians, statisticians, and computer scientists. The annual Neural Information Processing (NIPS) conference is the flagship meeting on neural computation. It draws a diverse group of attendees -- physicists, neuroscientists, mathematicians, statisticians, and computer scientists. The presentations are interdisciplinary, with contributions in algorithms, learning theory, cognitive science, neuroscience, brain imaging, vision, speech and signal processing, reinforcement learning and control, emerging technologies, and applications. Only thirty percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. This volume contains all the papers presented at the 2003 conference.

The Probability Companion for Engineering and Computer Science

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Publisher : Cambridge University Press
ISBN 13 : 1108573738
Total Pages : 475 pages
Book Rating : 4.1/5 (85 download)

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Book Synopsis The Probability Companion for Engineering and Computer Science by : Adam Prügel-Bennett

Download or read book The Probability Companion for Engineering and Computer Science written by Adam Prügel-Bennett and published by Cambridge University Press. This book was released on 2020-01-23 with total page 475 pages. Available in PDF, EPUB and Kindle. Book excerpt: This friendly guide is the companion you need to convert pure mathematics into understanding and facility with a host of probabilistic tools. The book provides a high-level view of probability and its most powerful applications. It begins with the basic rules of probability and quickly progresses to some of the most sophisticated modern techniques in use, including Kalman filters, Monte Carlo techniques, machine learning methods, Bayesian inference and stochastic processes. It draws on thirty years of experience in applying probabilistic methods to problems in computational science and engineering, and numerous practical examples illustrate where these techniques are used in the real world. Topics of discussion range from carbon dating to Wasserstein GANs, one of the most recent developments in Deep Learning. The underlying mathematics is presented in full, but clarity takes priority over complete rigour, making this text a starting reference source for researchers and a readable overview for students.

Advanced Statistical Mechanics

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Publisher : World Scientific
ISBN 13 : 981124216X
Total Pages : 225 pages
Book Rating : 4.8/5 (112 download)

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Book Synopsis Advanced Statistical Mechanics by : Jian-sheng Wang

Download or read book Advanced Statistical Mechanics written by Jian-sheng Wang and published by World Scientific. This book was released on 2021-11-03 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: This short textbook covers roughly 13 weeks of lectures on advanced statistical mechanics at the graduate level. It starts with an elementary introduction to the theory of ensembles from classical mechanics, and then goes on to quantum statistical mechanics with density matrix. These topics are covered concisely and briefly. The advanced topics cover the mean-field theory for phase transitions, the Ising models and their exact solutions, and critical phenomena and their scaling theory. The mean-field theories are discussed thoroughly with several different perspectives — focusing on a single degree, or using Feynman-Jensen-Bogoliubov inequality, cavity method, or Landau theory. The renormalization group theory is mentioned only briefly. As examples of computational and numerical approach, there is a chapter on Monte Carlo method including the cluster algorithms. The second half of the book studies nonequilibrium statistical mechanics, which includes the Brownian motion, the Langevin and Fokker-Planck equations, Boltzmann equation, linear response theory, and the Jarzynski equality. The book ends with a brief discussion of irreversibility. The topics are supplemented by problem sets (with partial answers) and supplementary readings up to the current research, such as heat transport with a Fokker-Planck approach.

Algorithmic Learning Theory

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Publisher : Springer
ISBN 13 : 3540302158
Total Pages : 519 pages
Book Rating : 4.5/5 (43 download)

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Book Synopsis Algorithmic Learning Theory by : Shai Ben David

Download or read book Algorithmic Learning Theory written by Shai Ben David and published by Springer. This book was released on 2004-09-24 with total page 519 pages. Available in PDF, EPUB and Kindle. Book excerpt: Algorithmic learning theory is mathematics about computer programs which learn from experience. This involves considerable interaction between various mathematical disciplines including theory of computation, statistics, and c- binatorics. There is also considerable interaction with the practical, empirical ?elds of machine and statistical learning in which a principal aim is to predict, from past data about phenomena, useful features of future data from the same phenomena. The papers in this volume cover a broad range of topics of current research in the ?eld of algorithmic learning theory. We have divided the 29 technical, contributed papers in this volume into eight categories (corresponding to eight sessions) re?ecting this broad range. The categories featured are Inductive Inf- ence, Approximate Optimization Algorithms, Online Sequence Prediction, S- tistical Analysis of Unlabeled Data, PAC Learning & Boosting, Statistical - pervisedLearning,LogicBasedLearning,andQuery&ReinforcementLearning. Below we give a brief overview of the ?eld, placing each of these topics in the general context of the ?eld. Formal models of automated learning re?ect various facets of the wide range of activities that can be viewed as learning. A ?rst dichotomy is between viewing learning as an inde?nite process and viewing it as a ?nite activity with a de?ned termination. Inductive Inference models focus on inde?nite learning processes, requiring only eventual success of the learner to converge to a satisfactory conclusion.

Machine Learning and Knowledge Discovery in Databases

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Publisher : Springer
ISBN 13 : 3642409911
Total Pages : 693 pages
Book Rating : 4.6/5 (424 download)

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Book Synopsis Machine Learning and Knowledge Discovery in Databases by : Hendrik Blockeel

Download or read book Machine Learning and Knowledge Discovery in Databases written by Hendrik Blockeel and published by Springer. This book was released on 2013-08-28 with total page 693 pages. Available in PDF, EPUB and Kindle. Book excerpt: This three-volume set LNAI 8188, 8189 and 8190 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2013, held in Prague, Czech Republic, in September 2013. The 111 revised research papers presented together with 5 invited talks were carefully reviewed and selected from 447 submissions. The papers are organized in topical sections on reinforcement learning; Markov decision processes; active learning and optimization; learning from sequences; time series and spatio-temporal data; data streams; graphs and networks; social network analysis; natural language processing and information extraction; ranking and recommender systems; matrix and tensor analysis; structured output prediction, multi-label and multi-task learning; transfer learning; bayesian learning; graphical models; nearest-neighbor methods; ensembles; statistical learning; semi-supervised learning; unsupervised learning; subgroup discovery, outlier detection and anomaly detection; privacy and security; evaluation; applications; and medical applications.

Advanced Wireless Networks

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Publisher : John Wiley & Sons
ISBN 13 : 1119096871
Total Pages : 864 pages
Book Rating : 4.1/5 (19 download)

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Book Synopsis Advanced Wireless Networks by : Savo G. Glisic

Download or read book Advanced Wireless Networks written by Savo G. Glisic and published by John Wiley & Sons. This book was released on 2016-07-22 with total page 864 pages. Available in PDF, EPUB and Kindle. Book excerpt: The third edition of this popular reference covers enabling technologies for building up 5G wireless networks. Due to extensive research and complexity of the incoming solutions for the next generation of wireless networks it is anticipated that the industry will select a subset of these results and leave some advanced technologies to be implemented later,. This new edition presents a carefully chosen combination of the candidate network architectures and the required tools for their analysis. Due to the complexity of the technology, the discussion on 5G will be extensive and it will be difficult to reach consensus on the new global standard. The discussion will have to include the vendors, operators, regulators as well as the research and academic community in the field. Having a comprehensive book will help many participants to join actively the discussion and make meaningful contribution to shaping the new standard.

Advanced Structured Prediction

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Publisher : MIT Press
ISBN 13 : 0262028379
Total Pages : 430 pages
Book Rating : 4.2/5 (62 download)

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Book Synopsis Advanced Structured Prediction by : Sebastian Nowozin

Download or read book Advanced Structured Prediction written by Sebastian Nowozin and published by MIT Press. This book was released on 2014-12-05 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: An overview of recent work in the field of structured prediction, the building of predictive machine learning models for interrelated and dependent outputs. The goal of structured prediction is to build machine learning models that predict relational information that itself has structure, such as being composed of multiple interrelated parts. These models, which reflect prior knowledge, task-specific relations, and constraints, are used in fields including computer vision, speech recognition, natural language processing, and computational biology. They can carry out such tasks as predicting a natural language sentence, or segmenting an image into meaningful components. These models are expressive and powerful, but exact computation is often intractable. A broad research effort in recent years has aimed at designing structured prediction models and approximate inference and learning procedures that are computationally efficient. This volume offers an overview of this recent research in order to make the work accessible to a broader research community. The chapters, by leading researchers in the field, cover a range of topics, including research trends, the linear programming relaxation approach, innovations in probabilistic modeling, recent theoretical progress, and resource-aware learning. Contributors Jonas Behr, Yutian Chen, Fernando De La Torre, Justin Domke, Peter V. Gehler, Andrew E. Gelfand, Sébastien Giguère, Amir Globerson, Fred A. Hamprecht, Minh Hoai, Tommi Jaakkola, Jeremy Jancsary, Joseph Keshet, Marius Kloft, Vladimir Kolmogorov, Christoph H. Lampert, François Laviolette, Xinghua Lou, Mario Marchand, André F. T. Martins, Ofer Meshi, Sebastian Nowozin, George Papandreou, Daniel Průša, Gunnar Rätsch, Amélie Rolland, Bogdan Savchynskyy, Stefan Schmidt, Thomas Schoenemann, Gabriele Schweikert, Ben Taskar, Sinisa Todorovic, Max Welling, David Weiss, Thomáš Werner, Alan Yuille, Stanislav Živný

Database Systems for Advanced Applications

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Publisher : Springer
ISBN 13 : 3319181238
Total Pages : 549 pages
Book Rating : 4.3/5 (191 download)

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Book Synopsis Database Systems for Advanced Applications by : Matthias Renz

Download or read book Database Systems for Advanced Applications written by Matthias Renz and published by Springer. This book was released on 2015-04-08 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two volume set LNCS 9049 and LNCS 9050 constitutes the refereed proceedings of the 20th International Conference on Database Systems for Advanced Applications, DASFAA 2015, held in Hanoi, Vietnam, in April 2015. The 63 full papers presented were carefully reviewed and selected from a total of 287 submissions. The papers cover the following topics: data mining; data streams and time series; database storage and index; spatio-temporal data; modern computing platform; social networks; information integration and data quality; information retrieval and summarization; security and privacy; outlier and imbalanced data analysis; probabilistic and uncertain data; query processing.

Mean Field Models for Spin Glasses

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Publisher :
ISBN 13 : 9783642152030
Total Pages : 504 pages
Book Rating : 4.1/5 (52 download)

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Book Synopsis Mean Field Models for Spin Glasses by : Michel Talagrand

Download or read book Mean Field Models for Spin Glasses written by Michel Talagrand and published by . This book was released on 2011 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: