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A Study On Online Variational Learning
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Book Synopsis Variational Bayesian Learning Theory by : Shinichi Nakajima
Download or read book Variational Bayesian Learning Theory written by Shinichi Nakajima and published by Cambridge University Press. This book was released on 2019-07-11 with total page 561 pages. Available in PDF, EPUB and Kindle. Book excerpt: This introduction to the theory of variational Bayesian learning summarizes recent developments and suggests practical applications.
Book Synopsis Mixture Models and Applications by : Nizar Bouguila
Download or read book Mixture Models and Applications written by Nizar Bouguila and published by Springer. This book was released on 2019-08-13 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on recent advances, approaches, theories and applications related to mixture models. In particular, it presents recent unsupervised and semi-supervised frameworks that consider mixture models as their main tool. The chapters considers mixture models involving several interesting and challenging problems such as parameters estimation, model selection, feature selection, etc. The goal of this book is to summarize the recent advances and modern approaches related to these problems. Each contributor presents novel research, a practical study, or novel applications based on mixture models, or a survey of the literature. Reports advances on classic problems in mixture modeling such as parameter estimation, model selection, and feature selection; Present theoretical and practical developments in mixture-based modeling and their importance in different applications; Discusses perspectives and challenging future works related to mixture modeling.
Book Synopsis Variational Methods for Machine Learning with Applications to Deep Networks by : Lucas Pinheiro Cinelli
Download or read book Variational Methods for Machine Learning with Applications to Deep Networks written by Lucas Pinheiro Cinelli and published by Springer Nature. This book was released on 2021-05-10 with total page 173 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a straightforward look at the concepts, algorithms and advantages of Bayesian Deep Learning and Deep Generative Models. Starting from the model-based approach to Machine Learning, the authors motivate Probabilistic Graphical Models and show how Bayesian inference naturally lends itself to this framework. The authors present detailed explanations of the main modern algorithms on variational approximations for Bayesian inference in neural networks. Each algorithm of this selected set develops a distinct aspect of the theory. The book builds from the ground-up well-known deep generative models, such as Variational Autoencoder and subsequent theoretical developments. By also exposing the main issues of the algorithms together with different methods to mitigate such issues, the book supplies the necessary knowledge on generative models for the reader to handle a wide range of data types: sequential or not, continuous or not, labelled or not. The book is self-contained, promptly covering all necessary theory so that the reader does not have to search for additional information elsewhere. Offers a concise self-contained resource, covering the basic concepts to the algorithms for Bayesian Deep Learning; Presents Statistical Inference concepts, offering a set of elucidative examples, practical aspects, and pseudo-codes; Every chapter includes hands-on examples and exercises and a website features lecture slides, additional examples, and other support material.
Book Synopsis An Introduction to Variational Autoencoders by : Diederik P. Kingma
Download or read book An Introduction to Variational Autoencoders written by Diederik P. Kingma and published by . This book was released on 2019-11-12 with total page 102 pages. Available in PDF, EPUB and Kindle. Book excerpt: An Introduction to Variational Autoencoders provides a quick summary for the of a topic that has become an important tool in modern-day deep learning techniques.
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.
Book Synopsis Spike-timing dependent plasticity by : Henry Markram
Download or read book Spike-timing dependent plasticity written by Henry Markram and published by Frontiers E-books. This book was released on with total page 575 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hebb's postulate provided a crucial framework to understand synaptic alterations underlying learning and memory. Hebb's theory proposed that neurons that fire together, also wire together, which provided the logical framework for the strengthening of synapses. Weakening of synapses was however addressed by "not being strengthened", and it was only later that the active decrease of synaptic strength was introduced through the discovery of long-term depression caused by low frequency stimulation of the presynaptic neuron. In 1994, it was found that the precise relative timing of pre and postynaptic spikes determined not only the magnitude, but also the direction of synaptic alterations when two neurons are active together. Neurons that fire together may therefore not necessarily wire together if the precise timing of the spikes involved are not tighly correlated. In the subsequent 15 years, Spike Timing Dependent Plasticity (STDP) has been found in multiple brain brain regions and in many different species. The size and shape of the time windows in which positive and negative changes can be made vary for different brain regions, but the core principle of spike timing dependent changes remain. A large number of theoretical studies have also been conducted during this period that explore the computational function of this driving principle and STDP algorithms have become the main learning algorithm when modeling neural networks. This Research Topic will bring together all the key experimental and theoretical research on STDP.
Author :R. Tyrrell Rockafellar Publisher :Springer Science & Business Media ISBN 13 :3642024319 Total Pages :747 pages Book Rating :4.6/5 (42 download)
Book Synopsis Variational Analysis by : R. Tyrrell Rockafellar
Download or read book Variational Analysis written by R. Tyrrell Rockafellar and published by Springer Science & Business Media. This book was released on 2009-06-26 with total page 747 pages. Available in PDF, EPUB and Kindle. Book excerpt: From its origins in the minimization of integral functionals, the notion of variations has evolved greatly in connection with applications in optimization, equilibrium, and control. This book develops a unified framework and provides a detailed exposition of variational geometry and subdifferential calculus in their current forms beyond classical and convex analysis. Also covered are set-convergence, set-valued mappings, epi-convergence, duality, and normal integrands.
Book Synopsis Variational and Quasi-Variational Inequalities in Mechanics by : Alexander S. Kravchuk
Download or read book Variational and Quasi-Variational Inequalities in Mechanics written by Alexander S. Kravchuk and published by Springer Science & Business Media. This book was released on 2007-09-04 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: The essential aim of this book is to consider a wide set of problems arising in the mathematical modeling of mechanical systems under unilateral constraints. In these investigations elastic and non-elastic deformations, friction and adhesion phenomena are taken into account. All the necessary mathematical tools are given: local boundary value problem formulations, construction of variational equations and inequalities and their transition to minimization problems, existence and uniqueness theorems, and variational transformations (Friedrichs and Young-Fenchel-Moreau) to dual and saddle-point search problems.
Book Synopsis Hidden Markov Models and Applications by : Nizar Bouguila
Download or read book Hidden Markov Models and Applications written by Nizar Bouguila and published by Springer Nature. This book was released on 2022-05-19 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on recent advances, approaches, theories, and applications related Hidden Markov Models (HMMs). In particular, the book presents recent inference frameworks and applications that consider HMMs. The authors discuss challenging problems that exist when considering HMMs for a specific task or application, such as estimation or selection, etc. The goal of this volume is to summarize the recent advances and modern approaches related to these problems. The book also reports advances on classic but difficult problems in HMMs such as inference and feature selection and describes real-world applications of HMMs from several domains. The book pertains to researchers and graduate students, who will gain a clear view of recent developments related to HMMs and their applications.
Book Synopsis Information Modelling and Knowledge Bases XXXI by : A. Dahanayake
Download or read book Information Modelling and Knowledge Bases XXXI written by A. Dahanayake and published by IOS Press. This book was released on 2020-01-06 with total page 562 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information modeling and knowledge bases have become an important area of academic and industry research in the 21st century, addressing complexities of modeling that reach beyond the traditional borders of information systems and academic computer science research. This book presents 32 reviewed, selected and updated papers delivered at the 29th International Conference on Information Modeling and Knowledge Bases (EJC2019), held in Lappeenranta, Finland, from 3 to 7 June 2019. In addition, two papers based on the keynote presentations and one paper edited from the discussion of the panel session are included in the book. The conference provided a forum to exchange scientific results and experience, and attracted academics and practitioners working with information and knowledge. The papers cover a wide range of topics, ranging from knowledge discovery through conceptual and linguistic modeling, knowledge and information modeling and discovery, cross-cultural communication and social computing, environmental modeling and engineering, and multimedia data modeling and systems to complex scientific problem-solving. The conference presentation sessions: Learning and Linguistics; Systems and Processes; Data and Knowledge Representation; Models and Interface; Formalizations and Reasoning; Models and Modeling; Machine Learning; Models and Programming; Environment and Predictions; and Emotion Modeling and Social Networks reflect the main themes of the conference. The book also includes 2 extended publications of keynote addresses: ‘Philosophical Foundations of Conceptual Modeling’ and ́Sustainable Solid Waste Management using Life Cycle Modeling for Environmental Impact Assessment’, as well as additional material covering the discussion and findings of the panel session. Providing an overview of current research in the field, the book will be of interest to all those working with information systems, information modeling and knowledge bases.
Book Synopsis Variational Methods by : Michael Struwe
Download or read book Variational Methods written by Michael Struwe and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hilbert's talk at the second International Congress of 1900 in Paris marked the beginning of a new era in the calculus of variations. A development began which, within a few decades, brought tremendous success, highlighted by the 1929 theorem of Ljusternik and Schnirelman on the existence of three distinct prime closed geodesics on any compact surface of genus zero, and the 1930/31 solution of Plateau's problem by Douglas and Radò. The book gives a concise introduction to variational methods and presents an overview of areas of current research in this field. This new edition has been substantially enlarged, a new chapter on the Yamabe problem has been added and the references have been updated. All topics are illustrated by carefully chosen examples, representing the current state of the art in their field.
Book Synopsis Lifelong Machine Learning, Second Edition by : Zhiyuan Sun
Download or read book Lifelong Machine Learning, Second Edition written by Zhiyuan Sun and published by Springer Nature. This book was released on 2022-06-01 with total page 187 pages. Available in PDF, EPUB and Kindle. Book excerpt: Lifelong Machine Learning, Second Edition is an introduction to an advanced machine learning paradigm that continuously learns by accumulating past knowledge that it then uses in future learning and problem solving. In contrast, the current dominant machine learning paradigm learns in isolation: given a training dataset, it runs a machine learning algorithm on the dataset to produce a model that is then used in its intended application. It makes no attempt to retain the learned knowledge and use it in subsequent learning. Unlike this isolated system, humans learn effectively with only a few examples precisely because our learning is very knowledge-driven: the knowledge learned in the past helps us learn new things with little data or effort. Lifelong learning aims to emulate this capability, because without it, an AI system cannot be considered truly intelligent. Research in lifelong learning has developed significantly in the relatively short time since the first edition of this book was published. The purpose of this second edition is to expand the definition of lifelong learning, update the content of several chapters, and add a new chapter about continual learning in deep neural networks—which has been actively researched over the past two or three years. A few chapters have also been reorganized to make each of them more coherent for the reader. Moreover, the authors want to propose a unified framework for the research area. Currently, there are several research topics in machine learning that are closely related to lifelong learning—most notably, multi-task learning, transfer learning, and meta-learning—because they also employ the idea of knowledge sharing and transfer. This book brings all these topics under one roof and discusses their similarities and differences. Its goal is to introduce this emerging machine learning paradigm and present a comprehensive survey and review of the important research results and latest ideas in the area. This book is thus suitable for students, researchers, and practitioners who are interested in machine learning, data mining, natural language processing, or pattern recognition. Lecturers can readily use the book for courses in any of these related fields.
Book Synopsis Adaptive and Intelligent Systems by : Abdelhamid Bouchachia
Download or read book Adaptive and Intelligent Systems written by Abdelhamid Bouchachia and published by Springer. This book was released on 2014-08-13 with total page 207 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the International Conference on Adaptive and Intelligent Systems, ICAIS 2014, held in Bournemouth, UK, in September 2014. The 19 full papers included in these proceedings together with the abstracts of 4 invited talks, were carefully reviewed and selected from 32 submissions. The contributions are organized under the following topical sections: advances in feature selection; clustering and classification; adaptive optimization; advances in time series analysis.
Book Synopsis Variational Methods in Imaging by : Otmar Scherzer
Download or read book Variational Methods in Imaging written by Otmar Scherzer and published by Springer Science & Business Media. This book was released on 2008-09-26 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is devoted to the study of variational methods in imaging. The presentation is mathematically rigorous and covers a detailed treatment of the approach from an inverse problems point of view. Many numerical examples accompany the theory throughout the text. It is geared towards graduate students and researchers in applied mathematics. Researchers in the area of imaging science will also find this book appealing. It can serve as a main text in courses in image processing or as a supplemental text for courses on regularization and inverse problems at the graduate level.
Book Synopsis Variational Techniques for Elliptic Partial Differential Equations by : Francisco J. Sayas
Download or read book Variational Techniques for Elliptic Partial Differential Equations written by Francisco J. Sayas and published by CRC Press. This book was released on 2019-01-16 with total page 492 pages. Available in PDF, EPUB and Kindle. Book excerpt: Variational Techniques for Elliptic Partial Differential Equations, intended for graduate students studying applied math, analysis, and/or numerical analysis, provides the necessary tools to understand the structure and solvability of elliptic partial differential equations. Beginning with the necessary definitions and theorems from distribution theory, the book gradually builds the functional analytic framework for studying elliptic PDE using variational formulations. Rather than introducing all of the prerequisites in the first chapters, it is the introduction of new problems which motivates the development of the associated analytical tools. In this way the student who is encountering this material for the first time will be aware of exactly what theory is needed, and for which problems. Features A detailed and rigorous development of the theory of Sobolev spaces on Lipschitz domains, including the trace operator and the normal component of vector fields An integration of functional analysis concepts involving Hilbert spaces and the problems which can be solved with these concepts, rather than separating the two Introduction to the analytical tools needed for physical problems of interest like time-harmonic waves, Stokes and Darcy flow, surface differential equations, Maxwell cavity problems, etc. A variety of problems which serve to reinforce and expand upon the material in each chapter, including applications in fluid and solid mechanics
Download or read book Data Clustering written by and published by BoD – Books on Demand. This book was released on 2022-08-17 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: In view of the considerable applications of data clustering techniques in various fields, such as engineering, artificial intelligence, machine learning, clinical medicine, biology, ecology, disease diagnosis, and business marketing, many data clustering algorithms and methods have been developed to deal with complicated data. These techniques include supervised learning methods and unsupervised learning methods such as density-based clustering, K-means clustering, and K-nearest neighbor clustering. This book reviews recently developed data clustering techniques and algorithms and discusses the development of data clustering, including measures of similarity or dissimilarity for data clustering, data clustering algorithms, assessment of clustering algorithms, and data clustering methods recently developed for insurance, psychology, pattern recognition, and survey data.
Book Synopsis Bayesian Theory and Applications by : Paul Damien
Download or read book Bayesian Theory and Applications written by Paul Damien and published by Oxford University Press. This book was released on 2013-01-24 with total page 717 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume guides the reader along a statistical journey that begins with the basic structure of Bayesian theory, and then provides details on most of the past and present advances in this field.
