Download or read book Simulated Annealing and Boltzmann Machines written by Emile H. L. Aarts and published by John Wiley & Sons. This book was released on 1989 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: Wiley-Interscience Series in Discrete Mathematics and Optimization Advisory Editors Ronald L. Graham Jan Karel Lenstra Robert E. Tarjan Discrete Mathematics and Optimization involves the study of finite structures. It is one of the fastest growing areas in mathematics today. The level and depth of recent advances in the area and the wide applicability of its evolving techniques point to the rapidity with which the field is moving from its beginnings to maturity and presage the ever-increasing interaction between it and computer science. The Series provides a broad coverage of discrete mathematics and optimization, ranging over such fields as combinatorics, graph theory, enumeration, mathematical programming and the analysis of algorithms, and including such topics as Ramsey theory, transversal theory, block designs, finite geometries, Polya theory, graph and matroid algorithms, network flows, polyhedral combinatorics and computational complexity. The Wiley - Interscience Series in Discrete Mathematics and Optimization will be a substantial part of the record of this extraordinary development. Recent titles in the Series: Search Problems Rudolf Ahlswede, University of Bielefeld, Federal Republic of Germany Ingo Wegener, Johann Wolfgang Goethe University, Frankfurt, Federal Republic of Germany The problems of search, exploration, discovery and identification are of key importance in a wide variety of applications. This book will be of great interest to all those concerned with searching, sorting, information processing, design of experiments and optimal allocation of resources. 1987 Introduction to Optimization E. M. L. Beale FRS, Scicon Ltd, Milton Keynes, and Imperial College, London This book is intended as an introduction to the many topics covered by the term 'optimization', with special emphasis on applications in industry. It is divided into three parts. The first part covers unconstrained optimization, the second describes the methods used to solve linear programming problems, and the third covers nonlinear programming, integer programming and dynamic programming. The book is intended for senior undergraduate and graduate students studying optimization as part of a course in mathematics, computer science or engineering. 1988

Download or read book Simulated annealing and boltzmann machines A stochastic approach to combinatorial optimization and neural computing written by AARTS / KORST. and published by . This book was released on 1990 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Simulated Annealing Theory and Applications written by P.J. van Laarhoven and published by Springer Science & Business Media. This book was released on 1987-06-30 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: It isn't that they can't see the solution. It is Approach your problems from the right end and begin with the answers. Then one day, that they can't see the problem. perhaps you will find the final question. O. K. Chesterton. The Scandal of Father 'The Hermit Clad in Crane Feathers' in R. Brown 'The point of a Pin'. van Oulik's The Chinese Maze Murders. Growing specialization and diversification have brought a host of monographs and textbooks or increasingly specialized topics. However, the "tree" of knowledg~ of mathematics and related fields does not grow only by putting forth new branches. It also ·happens, quite often in fact, that branches which were thought to be completely disparate are suddenly seen to be related. Further, the ~d and level of sophistication of mathematics applied in various sciences has changed drastically in recent years: measure theory is used (non-trivially) in regional and theoretical economics; algebraic geometry interacts with physics; the Minkowsky lemma, coding theory and the structure of water meet one another in packing and covering theory; quantum fields, crystal defects and mathematical programming profit from homotopy theory; Lie algebras are relevant to filtering; and prediction and electrical engineering can use Stein spaces. And in addition to this there are such new emerging subdisciplines as "experimental mathematics", "CFD", "completely integrable systems", "chaos, synergetics and large-scale order", which are almost impossible to fit into the existing classification schemes. They draw upon widely different sections of mathematics.

Download or read book Simulated Annealing and Stochastic Learning in Optical Neural Nets written by Zon-Yin Shae and published by . This book was released on 1989 with total page 534 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Genetic Algorithms and Simulated Annealing written by Lawrence Davis and published by Pitman Publishing. This book was released on 1987 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Simulated Annealing written by Marcos Sales Guerra Tsuzuki and published by BoD – Books on Demand. This book was released on 2012-10-17 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents state of the art contributes to Simulated Annealing (SA) that is a well-known probabilistic meta-heuristic. It is used to solve discrete and continuous optimization problems. The significant advantage of SA over other solution methods has made it a practical solution method for solving complex optimization problems. Book is consisted of 13 chapters, classified in single and multiple objectives applications and it provides the reader with the knowledge of SA and several applications. We encourage readers to explore SA in their work, mainly because it is simple and can determine extremely very good results.

Download or read book Hands On Machine Learning on Google Cloud Platform written by Giuseppe Ciaburro and published by Packt Publishing Ltd. This book was released on 2018-04-30 with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unleash Google's Cloud Platform to build, train and optimize machine learning models Key Features Get well versed in GCP pre-existing services to build your own smart models A comprehensive guide covering aspects from data processing, analyzing to building and training ML models A practical approach to produce your trained ML models and port them to your mobile for easy access Book Description Google Cloud Machine Learning Engine combines the services of Google Cloud Platform with the power and flexibility of TensorFlow. With this book, you will not only learn to build and train different complexities of machine learning models at scale but also host them in the cloud to make predictions. This book is focused on making the most of the Google Machine Learning Platform for large datasets and complex problems. You will learn from scratch how to create powerful machine learning based applications for a wide variety of problems by leveraging different data services from the Google Cloud Platform. Applications include NLP, Speech to text, Reinforcement learning, Time series, recommender systems, image classification, video content inference and many other. We will implement a wide variety of deep learning use cases and also make extensive use of data related services comprising the Google Cloud Platform ecosystem such as Firebase, Storage APIs, Datalab and so forth. This will enable you to integrate Machine Learning and data processing features into your web and mobile applications. By the end of this book, you will know the main difficulties that you may encounter and get appropriate strategies to overcome these difficulties and build efficient systems. What you will learn Use Google Cloud Platform to build data-based applications for dashboards, web, and mobile Create, train and optimize deep learning models for various data science problems on big data Learn how to leverage BigQuery to explore big datasets Use Google’s pre-trained TensorFlow models for NLP, image, video and much more Create models and architectures for Time series, Reinforcement Learning, and generative models Create, evaluate, and optimize TensorFlow and Keras models for a wide range of applications Who this book is for This book is for data scientists, machine learning developers and AI developers who want to learn Google Cloud Platform services to build machine learning applications. Since the interaction with the Google ML platform is mostly done via the command line, the reader is supposed to have some familiarity with the bash shell and Python scripting. Some understanding of machine learning and data science concepts will be handy

Download or read book The Boltzmann Machine A Survey and Generalization written by Mitchell Donn Eggers and published by . This book was released on 1988 with total page 53 pages. Available in PDF, EPUB and Kindle. Book excerpt: A tutorial is presented describing a general machine learning theory which spawns a class of energy minimizing machines useful in model identification, optimization, and associative memory. Special realizations of the theory include the Boltzmann machine and the Hopfield neural network. The theory is reinforced by appendices addressing particular facets of the machine, ranging from gradient descent to simulated annealing. The treatment is systematic, beginning with the description of the energy function. A defining relationship is established between the energy function and the optimal solution. Following, both classical and new learning algorithms are presented (directing the adaption of the free parameters) for numerically minimizing such function to yield the optimal solution. Finally, both computational burden and performance are assessed for several small-scale applications to date. Keywords: Neural networks, Boltzmann machine, Gibbs machine, Energy minimizing neural networks, Simulated annealing. (jhd).

Download or read book Neural Computation in Hopfield Networks and Boltzmann Machines written by James P. Coughlin and published by University of Delaware Press. This book was released on 1995 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: "One hundred years ago, the fundamental building block of the central nervous system, the neuron, was discovered. This study focuses on the existing mathematical models of neurons and their interactions, the simulation of which has been one of the biggest challenges facing modern science." "More than fifty years ago, W. S. McCulloch and W. Pitts devised their model for the neuron, John von Neumann seemed to sense the possibilities for the development of intelligent systems, and Frank Rosenblatt came up with a functioning network of neurons. Despite these advances, the subject had begun to fade as a major research area until John Hopfield arrived on the scene. Drawing an analogy between neural networks and the Ising spin models of ferromagnetism, Hopfield was able to introduce a "computational energy" that would decline toward stable minima under the operation of the system of neurodynamics devised by Roy Glauber." "Like a switch, a neuron is said to be either "on" or "off." The state of the neuron is determined by the states of the other neurons and the connections between them, and the connections are assumed to be reciprocal - that is, neuron number one influences neuron number two exactly as strongly as neuron number two influences neuron number one. According to the Glauber dynamics, the states of the neurons are updated in a random serial way until an equilibrium is reached. An energy function can be associated with each state, and equilibrium corresponds to a minimum of this energy. It follows from Hopfield's assumption of reciprocity that an equilibrium will always be reached." "D. H. Ackley, G. E. Hinton, and T. J. Sejnowski modified the Hopfield network by introducing the simulated annealing algorithm to search out the deepest minima. This is accomplished by - loosely speaking - shaking the machine. The violence of the shaking is controlled by a parameter called temperature, producing the Boltzmann machine - a name designed to emphasize the connection to the statistical physics of Ising spin models." "The Boltzmann machine reduces to the Hopfield model in the special case where the temperature goes to zero. The resulting network, under the Glauber dynamics, produces a homogeneous, irreducible, aperiodic Markov chain as it wanders through state space. The entire theory of Markov chains becomes applicable to the Boltzmann machine." "With ten chapters, five appendices, a list of references, and an index, this study should serve as an introduction to the field of neural networks and its application, and is suitable for an introductory graduate course or an advanced undergraduate course."--BOOK JACKET.Title Summary field provided by Blackwell North America, Inc. All Rights Reserved

Download or read book Fundamentals of Learning Algorithms in Boltzmann Machines written by Mihaela Georgeta Erbiceanu and published by . This book was released on 2016 with total page 155 pages. Available in PDF, EPUB and Kindle. Book excerpt: Boltzmann learning underlies an artificial neural network model known as the Boltzmann machine that extends and improves upon the Hopfield network model. Boltzmann machine model uses stochastic binary units and allows for the existence of hidden units to represent latent variables. When subjected to reducing noise via simulated annealing and allowing uphill steps via Metropolis algorithm, the training algorithm increases the chances that, at thermal equilibrium, the network settles on the best distribution of parameters. The existence of equilibrium distribution for an asynchronous Boltzmann machine is analyzed with respect to temperature. Two families of learning algorithms, which correspond to two different approaches to compute the statistics required for learning, are presented. The learning algorithms based only on stochastic approximations are traditionally slow. When variational approximations of the free energy are used, like the mean field approximation or the Bethe approximation, the performance of learning improves considerably. The principal contribution of the present study is to provide, from a rigorous mathematical perspective, a unified framework for these two families of learning algorithms in asynchronous Boltzmann machines.

Download or read book Applied Simulated Annealing written by Rene V.V. Vidal and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: In February 1992, I defended my doctoral thesis: Engineering Optimiza tion - selected contributions (IMSOR, The Technical University of Den mark, 1992, p. 92). This dissertation presents retrospectively my central contributions to the theoretical and applied aspects of optimization. When I had finished my thesis I became interested in editing a volume related to a new expanding area of applied optimization. I considered several approaches: simulated annealing, tabu search, genetic algorithms, neural networks, heuristics, expert systems, generalized multipliers, etc. Finally, I decided to edit a volume related to simulated annealing. My main three reasons for this choice were the following: (i) During the last four years my colleagues at IMSOR and I have car ried out several applied projects where simulated annealing was an essential. element in the problem-solving process. Most of the avail able reports and papers have been written in Danish. After a short review I was convinced that most of these works deserved to be pub lished for a wider audience. (ii) After the first reported applications of simulated annealing (1983- 1985), a tremendous amount of theoretical and applied work have been published within many different disciplines. Thus, I believe that simulated annealing is an approach that deserves to be in the curricula of, e.g. Engineering, Physics, Operations Research, Math ematical Programming, Economics, System Sciences, etc. (iii) A contact to an international network of well-known researchers showed that several individuals were willing to contribute to such a volume.

Download or read book Data Association Techniques for Bearings only Multi target Tracking Using Simulated Annealing and Implemented with Boltzmann Machines written by Pei-yih Ting and published by . This book was released on 1992 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Computational Intelligence for Optimization written by Nirwan Ansari and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of optimization is interdisciplinary in nature, and has been making a significant impact on many disciplines. As a result, it is an indispensable tool for many practitioners in various fields. Conventional optimization techniques have been well established and widely published in many excellent textbooks. However, there are new techniques, such as neural networks, simulated anneal ing, stochastic machines, mean field theory, and genetic algorithms, which have been proven to be effective in solving global optimization problems. This book is intended to provide a technical description on the state-of-the-art development in advanced optimization techniques, specifically heuristic search, neural networks, simulated annealing, stochastic machines, mean field theory, and genetic algorithms, with emphasis on mathematical theory, implementa tion, and practical applications. The text is suitable for a first-year graduate course in electrical and computer engineering, computer science, and opera tional research programs. It may also be used as a reference for practicing engineers, scientists, operational researchers, and other specialists. This book is an outgrowth of a couple of special topic courses that we have been teaching for the past five years. In addition, it includes many results from our inter disciplinary research on the topic. The aforementioned advanced optimization techniques have received increasing attention over the last decade, but relatively few books have been produced.

Download or read book Conference Publication written by and published by . This book was released on 1995 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book American Journal of Mathematical and Management Sciences written by and published by . This book was released on 1988 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Neural Networks and Simulation Methods written by Wu and published by CRC Press. This book was released on 1993-12-14 with total page 452 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work explains network dynamics, learning paradigms, and computational capabilities of feedforward, self-organization, and feedback neural network models-addressing specific problems such as data fusion and data modeling. It goes on to describe a neural network simulation software package - USTCNET and gives some segments of the program.

Download or read book Handbook of Metaheuristics written by Fred W. Glover and published by Springer Science & Business Media. This book was released on 2006-04-11 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides both the research and practitioner communities with a comprehensive coverage of the metaheuristic methodologies that have proven to be successful in a wide variety of real-world problem settings. Moreover, it is these metaheuristic strategies that hold particular promise for success in the future. The various chapters serve as stand alone presentations giving both the necessary background underpinnings as well as practical guides for implementation.