Handbook Of Machine Learning For Computational Optimization

Author : Vishal Jain,Sapna Juneja,Abhinav Juneja,Ramani Kannan
Publisher : CRC Press
Page : 295 pages
File Size : 41,6 Mb
Release : 2021-11-02
Category : Technology & Engineering
ISBN : 9781000455670

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Handbook of Machine Learning for Computational Optimization by Vishal Jain,Sapna Juneja,Abhinav Juneja,Ramani Kannan Pdf

Focuses on new machine learning developments that can lead to newly developed applications Uses a predictive and futuristic approach which makes Machine Learning a promising tool for business processes and sustainable solutions Promotes newer algorithms which are more efficient and reliable for a new dimension in discovering certain latent domains of applications Discusses the huge potential in making better use of machines in order to ensure optimal prediction, execution, and decision-making Offers many real-time case studies

Author : Tshilidzi Marwala,Collins Achepsah Leke
Publisher : World Scientific
Page : 321 pages
File Size : 41,7 Mb
Release : 2019-11-21
Category : Computers
ISBN : 9789811205682

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Handbook Of Machine Learning - Volume 2: Optimization And Decision Making by Tshilidzi Marwala,Collins Achepsah Leke Pdf

Building on , this volume on Optimization and Decision Making covers a range of algorithms and their applications. Like the first volume, it provides a starting point for machine learning enthusiasts as a comprehensive guide on classical optimization methods. It also provides an in-depth overview on how artificial intelligence can be used to define, disprove or validate economic modeling and decision making concepts.

Author : Plamen Parvanov Angelov
Publisher : World Scientific
Page : 1057 pages
File Size : 47,9 Mb
Release : 2022-06-29
Category : Computers
ISBN : 9789811247330

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Handbook On Computer Learning And Intelligence (In 2 Volumes) by Plamen Parvanov Angelov Pdf

The Handbook on Computer Learning and Intelligence is a second edition which aims to be a one-stop-shop for the various aspects of the broad research area of computer learning and intelligence. This field of research evolved so much in the last five years that it necessitates this new edition of the earlier Handbook on Computational Intelligence.This two-volume handbook is divided into five parts. Volume 1 covers Explainable AI and Supervised Learning. Volume 2 covers three parts: Deep Learning, Intelligent Control, and Evolutionary Computation. The chapters detail the theory, methodology and applications of computer learning and intelligence, and are authored by some of the leading experts in the respective areas. The fifteen core chapters of the previous edition have been written and significantly refreshed by the same authors. Parts of the handbook have evolved to keep pace with the latest developments in computational intelligence in the areas that span across Machine Learning and Artificial Intelligence. The Handbook remains dedicated to applications and engineering-orientated aspects of these areas over abstract theories.Related Link(s)

Author : Pijush Samui,Sanjiban Sekhar Roy,Valentina E. Balas
Publisher : Academic Press
Page : 658 pages
File Size : 50,9 Mb
Release : 2017-07-18
Category : Technology & Engineering
ISBN : 9780128113196

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Handbook of Neural Computation by Pijush Samui,Sanjiban Sekhar Roy,Valentina E. Balas Pdf

Handbook of Neural Computation explores neural computation applications, ranging from conventional fields of mechanical and civil engineering, to electronics, electrical engineering and computer science. This book covers the numerous applications of artificial and deep neural networks and their uses in learning machines, including image and speech recognition, natural language processing and risk analysis. Edited by renowned authorities in this field, this work is comprised of articles from reputable industry and academic scholars and experts from around the world. Each contributor presents a specific research issue with its recent and future trends. As the demand rises in the engineering and medical industries for neural networks and other machine learning methods to solve different types of operations, such as data prediction, classification of images, analysis of big data, and intelligent decision-making, this book provides readers with the latest, cutting-edge research in one comprehensive text. Features high-quality research articles on multivariate adaptive regression splines, the minimax probability machine, and more Discusses machine learning techniques, including classification, clustering, regression, web mining, information retrieval and natural language processing Covers supervised, unsupervised, reinforced, ensemble, and nature-inspired learning methods

Author : Suvrit Sra,Sebastian Nowozin,Stephen J. Wright
Publisher : MIT Press
Page : 509 pages
File Size : 52,8 Mb
Release : 2012
Category : Computers
ISBN : 9780262016469

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Optimization for Machine Learning by Suvrit Sra,Sebastian Nowozin,Stephen J. Wright Pdf

An up-to-date account of the interplay between optimization and machine learning, accessible to students and researchers in both communities. The interplay between optimization and machine learning is one of the most important developments in modern computational science. Optimization formulations and methods are proving to be vital in designing algorithms to extract essential knowledge from huge volumes of data. Machine learning, however, is not simply a consumer of optimization technology but a rapidly evolving field that is itself generating new optimization ideas. This book captures the state of the art of the interaction between optimization and machine learning in a way that is accessible to researchers in both fields. Optimization approaches have enjoyed prominence in machine learning because of their wide applicability and attractive theoretical properties. The increasing complexity, size, and variety of today's machine learning models call for the reassessment of existing assumptions. This book starts the process of reassessment. It describes the resurgence in novel contexts of established frameworks such as first-order methods, stochastic approximations, convex relaxations, interior-point methods, and proximal methods. It also devotes attention to newer themes such as regularized optimization, robust optimization, gradient and subgradient methods, splitting techniques, and second-order methods. Many of these techniques draw inspiration from other fields, including operations research, theoretical computer science, and subfields of optimization. The book will enrich the ongoing cross-fertilization between the machine learning community and these other fields, and within the broader optimization community.

Author : Janusz Kacprzyk,Witold Pedrycz
Publisher : Springer
Page : 1634 pages
File Size : 47,9 Mb
Release : 2015-05-28
Category : Technology & Engineering
ISBN : 9783662435052

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Springer Handbook of Computational Intelligence by Janusz Kacprzyk,Witold Pedrycz Pdf

The Springer Handbook for Computational Intelligence is the first book covering the basics, the state-of-the-art and important applications of the dynamic and rapidly expanding discipline of computational intelligence. This comprehensive handbook makes readers familiar with a broad spectrum of approaches to solve various problems in science and technology. Possible approaches include, for example, those being inspired by biology, living organisms and animate systems. Content is organized in seven parts: foundations; fuzzy logic; rough sets; evolutionary computation; neural networks; swarm intelligence and hybrid computational intelligence systems. Each Part is supervised by its own Part Editor(s) so that high-quality content as well as completeness are assured.

Author : Tshilidzi Marwala,Collins Achepsah Leke
Publisher : Unknown
Page : 128 pages
File Size : 40,6 Mb
Release : 2020
Category : Decision making
ISBN : 9811205671

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Handbook of Machine Learning by Tshilidzi Marwala,Collins Achepsah Leke Pdf

Author : Olivas, Emilio Soria,Guerrero, Jos‚ David Mart¡n,Martinez-Sober, Marcelino,Magdalena-Benedito, Jose Rafael,Serrano L¢pez, Antonio Jos‚
Publisher : IGI Global
Page : 852 pages
File Size : 41,8 Mb
Release : 2009-08-31
Category : Computers
ISBN : 9781605667676

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Handbook of Research on Machine Learning Applications and Trends: Algorithms, Methods, and Techniques by Olivas, Emilio Soria,Guerrero, Jos‚ David Mart¡n,Martinez-Sober, Marcelino,Magdalena-Benedito, Jose Rafael,Serrano L¢pez, Antonio Jos‚ Pdf

"This book investiges machine learning (ML), one of the most fruitful fields of current research, both in the proposal of new techniques and theoretic algorithms and in their application to real-life problems"--Provided by publisher.

Author : Tshilidzi Marwala
Publisher : World Scientific
Page : 329 pages
File Size : 55,6 Mb
Release : 2018-10-22
Category : Computers
ISBN : 9789813271241

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Handbook Of Machine Learning - Volume 1: Foundation Of Artificial Intelligence by Tshilidzi Marwala Pdf

This is a comprehensive book on the theories of artificial intelligence with an emphasis on their applications. It combines fuzzy logic and neural networks, as well as hidden Markov models and genetic algorithm, describes advancements and applications of these machine learning techniques and describes the problem of causality. This book should serves as a useful reference for practitioners in artificial intelligence.

Author : Solanki, Arun,Kumar, Sandeep,Nayyar, Anand
Publisher : IGI Global
Page : 674 pages
File Size : 55,8 Mb
Release : 2019-12-13
Category : Computers
ISBN : 9781522596455

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Handbook of Research on Emerging Trends and Applications of Machine Learning by Solanki, Arun,Kumar, Sandeep,Nayyar, Anand Pdf

As today’s world continues to advance, Artificial Intelligence (AI) is a field that has become a staple of technological development and led to the advancement of numerous professional industries. An application within AI that has gained attention is machine learning. Machine learning uses statistical techniques and algorithms to give computer systems the ability to understand and its popularity has circulated through many trades. Understanding this technology and its countless implementations is pivotal for scientists and researchers across the world. The Handbook of Research on Emerging Trends and Applications of Machine Learning provides a high-level understanding of various machine learning algorithms along with modern tools and techniques using Artificial Intelligence. In addition, this book explores the critical role that machine learning plays in a variety of professional fields including healthcare, business, and computer science. While highlighting topics including image processing, predictive analytics, and smart grid management, this book is ideally designed for developers, data scientists, business analysts, information architects, finance agents, healthcare professionals, researchers, retail traders, professors, and graduate students seeking current research on the benefits, implementations, and trends of machine learning.

Author : Charu C. Aggarwal
Publisher : Springer Nature
Page : 507 pages
File Size : 51,5 Mb
Release : 2020-05-13
Category : Computers
ISBN : 9783030403447

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Linear Algebra and Optimization for Machine Learning by Charu C. Aggarwal Pdf

This textbook introduces linear algebra and optimization in the context of machine learning. Examples and exercises are provided throughout the book. A solution manual for the exercises at the end of each chapter is available to teaching instructors. This textbook targets graduate level students and professors in computer science, mathematics and data science. Advanced undergraduate students can also use this textbook. The chapters for this textbook are organized as follows: 1. Linear algebra and its applications: The chapters focus on the basics of linear algebra together with their common applications to singular value decomposition, matrix factorization, similarity matrices (kernel methods), and graph analysis. Numerous machine learning applications have been used as examples, such as spectral clustering, kernel-based classification, and outlier detection. The tight integration of linear algebra methods with examples from machine learning differentiates this book from generic volumes on linear algebra. The focus is clearly on the most relevant aspects of linear algebra for machine learning and to teach readers how to apply these concepts. 2. Optimization and its applications: Much of machine learning is posed as an optimization problem in which we try to maximize the accuracy of regression and classification models. The “parent problem” of optimization-centric machine learning is least-squares regression. Interestingly, this problem arises in both linear algebra and optimization, and is one of the key connecting problems of the two fields. Least-squares regression is also the starting point for support vector machines, logistic regression, and recommender systems. Furthermore, the methods for dimensionality reduction and matrix factorization also require the development of optimization methods. A general view of optimization in computational graphs is discussed together with its applications to back propagation in neural networks. A frequent challenge faced by beginners in machine learning is the extensive background required in linear algebra and optimization. One problem is that the existing linear algebra and optimization courses are not specific to machine learning; therefore, one would typically have to complete more course material than is necessary to pick up machine learning. Furthermore, certain types of ideas and tricks from optimization and linear algebra recur more frequently in machine learning than other application-centric settings. Therefore, there is significant value in developing a view of linear algebra and optimization that is better suited to the specific perspective of machine learning.

Author : Jennie Si,Andrew G. Barto,Warren B. Powell,Don Wunsch
Publisher : John Wiley & Sons
Page : 670 pages
File Size : 53,7 Mb
Release : 2004-08-02
Category : Technology & Engineering
ISBN : 047166054X

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Handbook of Learning and Approximate Dynamic Programming by Jennie Si,Andrew G. Barto,Warren B. Powell,Don Wunsch Pdf

A complete resource to Approximate Dynamic Programming (ADP), including on-line simulation code Provides a tutorial that readers can use to start implementing the learning algorithms provided in the book Includes ideas, directions, and recent results on current research issues and addresses applications where ADP has been successfully implemented The contributors are leading researchers in the field

Author : Hassanien, Aboul Ella,Gaber, Tarek
Publisher : IGI Global
Page : 1093 pages
File Size : 43,7 Mb
Release : 2017-04-03
Category : Computers
ISBN : 9781522522300

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Handbook of Research on Machine Learning Innovations and Trends by Hassanien, Aboul Ella,Gaber, Tarek Pdf

Continuous improvements in technological applications have allowed more opportunities to develop automated systems. This not only leads to higher success in smart data analysis, but it increases the overall probability of technological progression. The Handbook of Research on Machine Learning Innovations and Trends is a key resource on the latest advances and research regarding the vast range of advanced systems and applications involved in machine intelligence. Highlighting multidisciplinary studies on decision theory, intelligent search, and multi-agent systems, this publication is an ideal reference source for professionals and researchers working in the field of machine learning and its applications.

Author : Kyriakos G. Vamvoudakis,Yan Wan,Frank L. Lewis,Derya Cansever
Publisher : Springer Nature
Page : 833 pages
File Size : 55,7 Mb
Release : 2021-06-23
Category : Technology & Engineering
ISBN : 9783030609900

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Handbook of Reinforcement Learning and Control by Kyriakos G. Vamvoudakis,Yan Wan,Frank L. Lewis,Derya Cansever Pdf

This handbook presents state-of-the-art research in reinforcement learning, focusing on its applications in the control and game theory of dynamic systems and future directions for related research and technology. The contributions gathered in this book deal with challenges faced when using learning and adaptation methods to solve academic and industrial problems, such as optimization in dynamic environments with single and multiple agents, convergence and performance analysis, and online implementation. They explore means by which these difficulties can be solved, and cover a wide range of related topics including: deep learning; artificial intelligence; applications of game theory; mixed modality learning; and multi-agent reinforcement learning. Practicing engineers and scholars in the field of machine learning, game theory, and autonomous control will find the Handbook of Reinforcement Learning and Control to be thought-provoking, instructive and informative.

Author : Angelov Plamen Parvanov
Publisher : World Scientific
Page : 964 pages
File Size : 51,7 Mb
Release : 2016-03-18
Category : Computers
ISBN : 9789814675024

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Handbook On Computational Intelligence (In 2 Volumes) by Angelov Plamen Parvanov Pdf

With the Internet, the proliferation of Big Data, and autonomous systems, mankind has entered into an era of 'digital obesity'. In this century, computational intelligence, such as thinking machines, have been brought forth to process complex human problems in a wide scope of areas — from social sciences, economics and biology, medicine and social networks, to cyber security.The Handbook of Computational Intelligence (in two volumes) prompts readers to look at these problems from a non-traditional angle. It takes a step by step approach, supported by case studies, to explore the issues that have arisen in the process. The Handbook covers many classic paradigms, as well as recent achievements and future promising developments to solve some of these very complex problems. Volume one explores the subjects of fuzzy logic and systems, artificial neural networks, and learning systems. Volume two delves into evolutionary computation, hybrid systems, as well as the applications of computational intelligence in decision making, the process industry, robotics, and autonomous systems.This work is a 'one-stop-shop' for beginners, as well as an inspirational source for more advanced researchers. It is a useful resource for lecturers and learners alike.