Combinatorial Machine Learning
DOWNLOAD
Download Combinatorial Machine Learning PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Combinatorial Machine Learning book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Combinatorial Machine Learning
DOWNLOAD
Author : Mikhail Moshkov
language : en
Publisher: Springer
Release Date : 2011-06-29
Combinatorial Machine Learning written by Mikhail Moshkov and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-06-29 with Computers categories.
Decision trees and decision rule systems are widely used in different applications as algorithms for problem solving, as predictors, and as a way for knowledge representation. Reducts play key role in the problem of attribute (feature) selection. The aims of this book are (i) the consideration of the sets of decision trees, rules and reducts; (ii) study of relationships among these objects; (iii) design of algorithms for construction of trees, rules and reducts; and (iv) obtaining bounds on their complexity. Applications for supervised machine learning, discrete optimization, analysis of acyclic programs, fault diagnosis, and pattern recognition are considered also. This is a mixture of research monograph and lecture notes. It contains many unpublished results. However, proofs are carefully selected to be understandable for students. The results considered in this book can be useful for researchers in machine learning, data mining and knowledge discovery, especially for those who are working in rough set theory, test theory and logical analysis of data. The book can be used in the creation of courses for graduate students.
Combinatorial Machine Learning
DOWNLOAD
Author : Mikhail Ju Moshkov
language : en
Publisher:
Release Date : 2011
Combinatorial Machine Learning written by Mikhail Ju Moshkov 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.
The Cross Entropy Method
DOWNLOAD
Author : Reuven Y. Rubinstein
language : en
Publisher: Springer Science & Business Media
Release Date : 2004-07-28
The Cross Entropy Method written by Reuven Y. Rubinstein 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 2004-07-28 with Business & Economics categories.
Rubinstein is the pioneer of the well-known score function and cross-entropy methods. Accessible to a broad audience of engineers, computer scientists, mathematicians, statisticians and in general anyone, theorist and practitioner, who is interested in smart simulation, fast optimization, learning algorithms, and image processing.
Nonlinear Combinatorial Optimization
DOWNLOAD
Author : Ding-Zhu Du
language : en
Publisher: Springer
Release Date : 2019-05-31
Nonlinear Combinatorial Optimization written by Ding-Zhu Du and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-31 with Mathematics categories.
Graduate students and researchers in applied mathematics, optimization, engineering, computer science, and management science will find this book a useful reference which provides an introduction to applications and fundamental theories in nonlinear combinatorial optimization. Nonlinear combinatorial optimization is a new research area within combinatorial optimization and includes numerous applications to technological developments, such as wireless communication, cloud computing, data science, and social networks. Theoretical developments including discrete Newton methods, primal-dual methods with convex relaxation, submodular optimization, discrete DC program, along with several applications are discussed and explored in this book through articles by leading experts.
Automated Design Of Machine Learning And Search Algorithms
DOWNLOAD
Author : Nelishia Pillay
language : en
Publisher: Springer Nature
Release Date : 2021-07-28
Automated Design Of Machine Learning And Search Algorithms written by Nelishia Pillay and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-28 with Computers categories.
This book presents recent advances in automated machine learning (AutoML) and automated algorithm design and indicates the future directions in this fast-developing area. Methods have been developed to automate the design of neural networks, heuristics and metaheuristics using techniques such as metaheuristics, statistical techniques, machine learning and hyper-heuristics. The book first defines the field of automated design, distinguishing it from the similar but different topics of automated algorithm configuration and automated algorithm selection. The chapters report on the current state of the art by experts in the field and include reviews of AutoML and automated design of search, theoretical analyses of automated algorithm design, automated design of control software for robot swarms, and overfitting as a benchmark and design tool. Also covered are automated generation of constructive and perturbative low-level heuristics, selection hyper-heuristics for automated design, automated design of deep-learning approaches using hyper-heuristics, genetic programming hyper-heuristics with transfer knowledge and automated design of classification algorithms. The book concludes by examining future research directions of this rapidly evolving field. The information presented here will especially interest researchers and practitioners in the fields of artificial intelligence, computational intelligence, evolutionary computation and optimisation.
Integer And Combinatorial Optimization
DOWNLOAD
Author : Laurence A. Wolsey
language : en
Publisher: John Wiley & Sons
Release Date : 2014-08-28
Integer And Combinatorial Optimization written by Laurence A. Wolsey and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-08-28 with Mathematics categories.
Rave reviews for INTEGER AND COMBINATORIAL OPTIMIZATION "This book provides an excellent introduction and survey of traditional fields of combinatorial optimization . . . It is indeed one of the best and most complete texts on combinatorial optimization . . . available. [And] with more than 700 entries, [it] has quite an exhaustive reference list."-Optima "A unifying approach to optimization problems is to formulate them like linear programming problems, while restricting some or all of the variables to the integers. This book is an encyclopedic resource for such formulations, as well as for understanding the structure of and solving the resulting integer programming problems."-Computing Reviews "[This book] can serve as a basis for various graduate courses on discrete optimization as well as a reference book for researchers and practitioners."-Mathematical Reviews "This comprehensive and wide-ranging book will undoubtedly become a standard reference book for all those in the field of combinatorial optimization."-Bulletin of the London Mathematical Society "This text should be required reading for anybody who intends to do research in this area or even just to keep abreast of developments."-Times Higher Education Supplement, London Also of interest . . . INTEGER PROGRAMMING Laurence A. Wolsey Comprehensive and self-contained, this intermediate-level guide to integer programming provides readers with clear, up-to-date explanations on why some problems are difficult to solve, how techniques can be reformulated to give better results, and how mixed integer programming systems can be used more effectively. 1998 (0-471-28366-5) 260 pp.
Machine Learning With Swift
DOWNLOAD
Author : Oleksandr Sosnovshchenko
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-02-28
Machine Learning With Swift written by Oleksandr Sosnovshchenko and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-02-28 with Computers categories.
Leverage the power of machine learning and Swift programming to build intelligent iOS applications with ease Key Features Implement effective machine learning solutions for your iOS applications Use Swift and Core ML to build and deploy popular machine learning models Develop neural networks for natural language processing and computer vision Book Description Machine learning as a field promises to bring increased intelligence to the software by helping us learn and analyse information efficiently and discover certain patterns that humans cannot. This book will be your guide as you embark on an exciting journey in machine learning using the popular Swift language. We’ll start with machine learning basics in the first part of the book to develop a lasting intuition about fundamental machine learning concepts. We explore various supervised and unsupervised statistical learning techniques and how to implement them in Swift, while the third section walks you through deep learning techniques with the help of typical real-world cases. In the last section, we will dive into some hard core topics such as model compression, GPU acceleration and provide some recommendations to avoid common mistakes during machine learning application development. By the end of the book, you'll be able to develop intelligent applications written in Swift that can learn for themselves. What you will learn Learn rapid model prototyping with Python and Swift Deploy pre-trained models to iOS using Core ML Find hidden patterns in the data using unsupervised learning Get a deeper understanding of the clustering techniques Learn modern compact architectures of neural networks for iOS devices Train neural networks for image processing and natural language processing Who this book is for iOS developers who wish to create smarter iOS applications using the power of machine learning will find this book to be useful. This book will also benefit data science professionals who are interested in performing machine learning on mobile devices. Familiarity with Swift programming is all you need to get started with this book.
Metaheuristics In Machine Learning Theory And Applications
DOWNLOAD
Author : Diego Oliva
language : en
Publisher: Springer Nature
Release Date : 2021-07-13
Metaheuristics In Machine Learning Theory And Applications written by Diego Oliva and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-13 with Computers categories.
This book is a collection of the most recent approaches that combine metaheuristics and machine learning. Some of the methods considered in this book are evolutionary, swarm, machine learning, and deep learning. The chapters were classified based on the content; then, the sections are thematic. Different applications and implementations are included; in this sense, the book provides theory and practical content with novel machine learning and metaheuristic algorithms. The chapters were compiled using a scientific perspective. Accordingly, the book is primarily intended for undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics and is useful in courses on Artificial Intelligence, Advanced Machine Learning, among others. Likewise, the book is useful for research from the evolutionary computation, artificial intelligence, and image processing communities.
Combinatorial Optimization
DOWNLOAD
Author : Christos H. Papadimitriou
language : en
Publisher: Courier Corporation
Release Date : 1998-01-01
Combinatorial Optimization written by Christos H. Papadimitriou and has been published by Courier Corporation this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-01-01 with Mathematics categories.
Clearly written graduate-level text considers the Soviet ellipsoid algorithm for linear programming; efficient algorithms for network flow, matching, spanning trees, and matroids; the theory of NP-complete problems; approximation algorithms, local search heuristics for NP-complete problems, more. "Mathematicians wishing a self-contained introduction need look no further." — American Mathematical Monthly. 1982 edition.
Handbook Of Metaheuristics
DOWNLOAD
Author : Michel Gendreau
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-09-11
Handbook Of Metaheuristics written by Michel Gendreau 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 2010-09-11 with Business & Economics categories.
The rst edition of the Handbook of Metaheuristics was published in 2003 under the editorship of Fred Glover and Gary A. Kochenberger. Given the numerous - velopments observed in the eld of metaheuristics in recent years, it appeared that the time was ripe for a second edition of the Handbook. For different reasons, Fred and Gary were unable to accept Springer’s invitation to prepare this second e- tion and they suggested that we should take over the editorship responsibility of the Handbook. We are deeply honored and grateful for their trust. As stated in the rst edition, metaheuristics are “solution methods that orch- trate an interaction between local improvement procedures and higher level stra- gies to create a process capable of escaping from local optima and performing a robust search of a solution space. ” Although this broad characterization still holds today, many new and exciting developments and extensions have been observed in the last few years. We think in particular to hybrids, which take advantage of the strengths of each of their individual metaheuristic components to better explore the solution space. Hybrids of metaheuristics with other optimization techniques, like branch-and-bound, mathematical programming or constraint programming are also increasingly popular. On the front of applications, metaheuristics are now used to nd high-quality solutions to an ever-growing number of complex, ill-de ned re- world problems, in particular combinatorial ones.