Open Problems In Optimization And Data Analysis

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Open Problems in Optimization and Data Analysis

Author : Panos M. Pardalos
Publisher : Springer
ISBN 13 : 3319991426
Total Pages : 330 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Open Problems in Optimization and Data Analysis by : Panos M. Pardalos

Download or read book Open Problems in Optimization and Data Analysis written by Panos M. Pardalos and published by Springer. This book was released on 2018-12-04 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational and theoretical open problems in optimization, computational geometry, data science, logistics, statistics, supply chain modeling, and data analysis are examined in this book. Each contribution provides the fundamentals needed to fully comprehend the impact of individual problems. Current theoretical, algorithmic, and practical methods used to circumvent each problem are provided to stimulate a new effort towards innovative and efficient solutions. Aimed towards graduate students and researchers in mathematics, optimization, operations research, quantitative logistics, data analysis, and statistics, this book provides a broad comprehensive approach to understanding the significance of specific challenging or open problems within each discipline. The contributions contained in this book are based on lectures focused on “Challenges and Open Problems in Optimization and Data Science” presented at the Deucalion Summer Institute for Advanced Studies in Optimization, Mathematics, and Data Science in August 2016.

Optimization for Data Analysis

Author : Stephen J. Wright
Publisher : Cambridge University Press
ISBN 13 : 1316518981
Total Pages : 239 pages
Book Rating : 4.3/5 (165 download)

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Book Synopsis Optimization for Data Analysis by : Stephen J. Wright

Download or read book Optimization for Data Analysis written by Stephen J. Wright and published by Cambridge University Press. This book was released on 2022-04-21 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: A concise text that presents and analyzes the fundamental techniques and methods in optimization that are useful in data science.

Optimization for Data Analysis

Author : Stephen J. Wright
Publisher : Cambridge University Press
ISBN 13 : 1009019120
Total Pages : 239 pages
Book Rating : 4.0/5 (9 download)

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Book Synopsis Optimization for Data Analysis by : Stephen J. Wright

Download or read book Optimization for Data Analysis written by Stephen J. Wright and published by Cambridge University Press. This book was released on 2022-04-21 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimization techniques are at the core of data science, including data analysis and machine learning. An understanding of basic optimization techniques and their fundamental properties provides important grounding for students, researchers, and practitioners in these areas. This text covers the fundamentals of optimization algorithms in a compact, self-contained way, focusing on the techniques most relevant to data science. An introductory chapter demonstrates that many standard problems in data science can be formulated as optimization problems. Next, many fundamental methods in optimization are described and analyzed, including: gradient and accelerated gradient methods for unconstrained optimization of smooth (especially convex) functions; the stochastic gradient method, a workhorse algorithm in machine learning; the coordinate descent approach; several key algorithms for constrained optimization problems; algorithms for minimizing nonsmooth functions arising in data science; foundations of the analysis of nonsmooth functions and optimization duality; and the back-propagation approach, relevant to neural networks.

Optimization and Its Applications in Control and Data Sciences

Author : Boris Goldengorin
Publisher : Springer
ISBN 13 : 3319420569
Total Pages : 516 pages
Book Rating : 4.3/5 (194 download)

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Book Synopsis Optimization and Its Applications in Control and Data Sciences by : Boris Goldengorin

Download or read book Optimization and Its Applications in Control and Data Sciences written by Boris Goldengorin and published by Springer. This book was released on 2016-09-29 with total page 516 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on recent research in modern optimization and its implications in control and data analysis. This book is a collection of papers from the conference “Optimization and Its Applications in Control and Data Science” dedicated to Professor Boris T. Polyak, which was held in Moscow, Russia on May 13-15, 2015. This book reflects developments in theory and applications rooted by Professor Polyak’s fundamental contributions to constrained and unconstrained optimization, differentiable and nonsmooth functions, control theory and approximation. Each paper focuses on techniques for solving complex optimization problems in different application areas and recent developments in optimization theory and methods. Open problems in optimization, game theory and control theory are included in this collection which will interest engineers and researchers working with efficient algorithms and software for solving optimization problems in market and data analysis. Theoreticians in operations research, applied mathematics, algorithm design, artificial intelligence, machine learning, and software engineering will find this book useful and graduate students will find the state-of-the-art research valuable.

Finite Algorithms in Optimization and Data Analysis

Author : M. R. Osborne
Publisher :
ISBN 13 :
Total Pages : 408 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Finite Algorithms in Optimization and Data Analysis by : M. R. Osborne

Download or read book Finite Algorithms in Optimization and Data Analysis written by M. R. Osborne and published by . This book was released on 1985-12-23 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: The significance and originality of this book derive from its novel approach to those optimization problems in which an active set strategy leads to a finite algorithm, such as linear and quadratic programming or l1 and l approximations.

Optimization Problems and Their Applications

Author : Anton Eremeev
Publisher : Springer
ISBN 13 : 3319938002
Total Pages : 343 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Optimization Problems and Their Applications by : Anton Eremeev

Download or read book Optimization Problems and Their Applications written by Anton Eremeev and published by Springer. This book was released on 2018-06-29 with total page 343 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes extended, revised and selected papers from the 7th International Conference on Optimization Problems and Their Applications, OPTA 2018, held in Omsk, Russia in July 2018. The 27 papers presented in this volume were carefully reviewed and selected from a total of 73 submissions. The papers are listed in thematic sections, namely location problems, scheduling and routing problems, optimization problems in data analysis, mathematical programming, game theory and economical applications, applied optimization problems and metaheuristics.

Linear Optimization Problems with Inexact Data

Author : Miroslav Fiedler
Publisher : Springer Science & Business Media
ISBN 13 : 0387326987
Total Pages : 222 pages
Book Rating : 4.3/5 (873 download)

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Book Synopsis Linear Optimization Problems with Inexact Data by : Miroslav Fiedler

Download or read book Linear Optimization Problems with Inexact Data written by Miroslav Fiedler and published by Springer Science & Business Media. This book was released on 2006-07-18 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: Linear programming has attracted the interest of mathematicians since World War II when the first computers were constructed. Early attempts to apply linear programming methods practical problems failed, in part because of the inexactness of the data used to create the models. This book presents a comprehensive treatment of linear optimization with inexact data, summarizing existing results and presenting new ones within a unifying framework.

Big Data Optimization: Recent Developments and Challenges

Author : Ali Emrouznejad
Publisher : Springer
ISBN 13 : 3319302655
Total Pages : 492 pages
Book Rating : 4.3/5 (193 download)

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Book Synopsis Big Data Optimization: Recent Developments and Challenges by : Ali Emrouznejad

Download or read book Big Data Optimization: Recent Developments and Challenges written by Ali Emrouznejad and published by Springer. This book was released on 2016-05-26 with total page 492 pages. Available in PDF, EPUB and Kindle. Book excerpt: The main objective of this book is to provide the necessary background to work with big data by introducing some novel optimization algorithms and codes capable of working in the big data setting as well as introducing some applications in big data optimization for both academics and practitioners interested, and to benefit society, industry, academia, and government. Presenting applications in a variety of industries, this book will be useful for the researchers aiming to analyses large scale data. Several optimization algorithms for big data including convergent parallel algorithms, limited memory bundle algorithm, diagonal bundle method, convergent parallel algorithms, network analytics, and many more have been explored in this book.

Algorithm Portfolios

Author : Dimitris Souravlias
Publisher : Springer Nature
ISBN 13 : 3030685144
Total Pages : 92 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Algorithm Portfolios by : Dimitris Souravlias

Download or read book Algorithm Portfolios written by Dimitris Souravlias and published by Springer Nature. This book was released on 2021-03-24 with total page 92 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers algorithm portfolios, multi-method schemes that harness optimization algorithms into a joint framework to solve optimization problems. It is expected to be a primary reference point for researchers and doctoral students in relevant domains that seek a quick exposure to the field. The presentation focuses primarily on the applicability of the methods and the non-expert reader will find this book useful for starting designing and implementing algorithm portfolios. The book familiarizes the reader with algorithm portfolios through current advances, applications, and open problems. Fundamental issues in building effective and efficient algorithm portfolios such as selection of constituent algorithms, allocation of computational resources, interaction between algorithms and parallelism vs. sequential implementations are discussed. Several new applications are analyzed and insights on the underlying algorithmic designs are provided. Future directions, new challenges, and open problems in the design of algorithm portfolios and applications are explored to further motivate research in this field.

Experimental Algorithms

Author : Panos M. Pardalos
Publisher : Springer
ISBN 13 : 364220662X
Total Pages : 469 pages
Book Rating : 4.6/5 (422 download)

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Book Synopsis Experimental Algorithms by : Panos M. Pardalos

Download or read book Experimental Algorithms written by Panos M. Pardalos and published by Springer. This book was released on 2011-04-21 with total page 469 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume constitutes the refereed proceedings of the 10th International Symposium on Experimental Algorithms, SEA 2011, held in Kolimpari, Chania, Crete, Greece, in May 2011. The 36 revised full papers presented together with 2 invited papers were carefully reviewed and selected from 83 submissions and present current research in the area of design, analysis, and experimental evaluation and engineering of algorithms, as well as in various aspects of computational optimization and its applications.

Convex Optimization

Author : Stephen P. Boyd
Publisher : Cambridge University Press
ISBN 13 : 9780521833783
Total Pages : 744 pages
Book Rating : 4.8/5 (337 download)

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Book Synopsis Convex Optimization by : Stephen P. Boyd

Download or read book Convex Optimization written by Stephen P. Boyd and published by Cambridge University Press. This book was released on 2004-03-08 with total page 744 pages. Available in PDF, EPUB and Kindle. Book excerpt: Convex optimization problems arise frequently in many different fields. This book provides a comprehensive introduction to the subject, and shows in detail how such problems can be solved numerically with great efficiency. The book begins with the basic elements of convex sets and functions, and then describes various classes of convex optimization problems. Duality and approximation techniques are then covered, as are statistical estimation techniques. Various geometrical problems are then presented, and there is detailed discussion of unconstrained and constrained minimization problems, and interior-point methods. The focus of the book is on recognizing convex optimization problems and then finding the most appropriate technique for solving them. It contains many worked examples and homework exercises and will appeal to students, researchers and practitioners in fields such as engineering, computer science, mathematics, statistics, finance and economics.

Perturbation Analysis of Optimization Problems

Author : J.Frederic Bonnans
Publisher : Springer Science & Business Media
ISBN 13 : 1461213940
Total Pages : 618 pages
Book Rating : 4.4/5 (612 download)

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Book Synopsis Perturbation Analysis of Optimization Problems by : J.Frederic Bonnans

Download or read book Perturbation Analysis of Optimization Problems written by J.Frederic Bonnans and published by Springer Science & Business Media. This book was released on 2013-11-22 with total page 618 pages. Available in PDF, EPUB and Kindle. Book excerpt: A presentation of general results for discussing local optimality and computation of the expansion of value function and approximate solution of optimization problems, followed by their application to various fields, from physics to economics. The book is thus an opportunity for popularizing these techniques among researchers involved in other sciences, including users of optimization in a wide sense, in mechanics, physics, statistics, finance and economics. Of use to research professionals, including graduate students at an advanced level.

Some optimization problems in data analysis

Author : William Gerrard McGinley
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (258 download)

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Book Synopsis Some optimization problems in data analysis by : William Gerrard McGinley

Download or read book Some optimization problems in data analysis written by William Gerrard McGinley and published by . This book was released on 1977 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Optimization Problems in Graph Theory

Author : Boris Goldengorin
Publisher : Springer
ISBN 13 : 331994830X
Total Pages : 331 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Optimization Problems in Graph Theory by : Boris Goldengorin

Download or read book Optimization Problems in Graph Theory written by Boris Goldengorin and published by Springer. This book was released on 2018-09-27 with total page 331 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents open optimization problems in graph theory and networks. Each chapter reflects developments in theory and applications based on Gregory Gutin’s fundamental contributions to advanced methods and techniques in combinatorial optimization. Researchers, students, and engineers in computer science, big data, applied mathematics, operations research, algorithm design, artificial intelligence, software engineering, data analysis, industrial and systems engineering will benefit from the state-of-the-art results presented in modern graph theory and its applications to the design of efficient algorithms for optimization problems. Topics covered in this work include: · Algorithmic aspects of problems with disjoint cycles in graphs · Graphs where maximal cliques and stable sets intersect · The maximum independent set problem with special classes · A general technique for heuristic algorithms for optimization problems · The network design problem with cut constraints · Algorithms for computing the frustration index of a signed graph · A heuristic approach for studying the patrol problem on a graph · Minimum possible sum and product of the proper connection number · Structural and algorithmic results on branchings in digraphs · Improved upper bounds for Korkel--Ghosh benchmark SPLP instances

Mathematical Problems in Data Science

Author : Li M. Chen
Publisher : Springer
ISBN 13 : 3319251279
Total Pages : 219 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis Mathematical Problems in Data Science by : Li M. Chen

Download or read book Mathematical Problems in Data Science written by Li M. Chen and published by Springer. This book was released on 2015-12-15 with total page 219 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes current problems in data science and Big Data. Key topics are data classification, Graph Cut, the Laplacian Matrix, Google Page Rank, efficient algorithms, hardness of problems, different types of big data, geometric data structures, topological data processing, and various learning methods. For unsolved problems such as incomplete data relation and reconstruction, the book includes possible solutions and both statistical and computational methods for data analysis. Initial chapters focus on exploring the properties of incomplete data sets and partial-connectedness among data points or data sets. Discussions also cover the completion problem of Netflix matrix; machine learning method on massive data sets; image segmentation and video search. This book introduces software tools for data science and Big Data such MapReduce, Hadoop, and Spark. This book contains three parts. The first part explores the fundamental tools of data science. It includes basic graph theoretical methods, statistical and AI methods for massive data sets. In second part, chapters focus on the procedural treatment of data science problems including machine learning methods, mathematical image and video processing, topological data analysis, and statistical methods. The final section provides case studies on special topics in variational learning, manifold learning, business and financial data rec overy, geometric search, and computing models. Mathematical Problems in Data Science is a valuable resource for researchers and professionals working in data science, information systems and networks. Advanced-level students studying computer science, electrical engineering and mathematics will also find the content helpful.

Frontiers in Massive Data Analysis

Author : National Research Council
Publisher : National Academies Press
ISBN 13 : 0309287812
Total Pages : 191 pages
Book Rating : 4.3/5 (92 download)

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Book Synopsis Frontiers in Massive Data Analysis by : National Research Council

Download or read book Frontiers in Massive Data Analysis written by National Research Council and published by National Academies Press. This book was released on 2013-09-03 with total page 191 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data mining of massive data sets is transforming the way we think about crisis response, marketing, entertainment, cybersecurity and national intelligence. Collections of documents, images, videos, and networks are being thought of not merely as bit strings to be stored, indexed, and retrieved, but as potential sources of discovery and knowledge, requiring sophisticated analysis techniques that go far beyond classical indexing and keyword counting, aiming to find relational and semantic interpretations of the phenomena underlying the data. Frontiers in Massive Data Analysis examines the frontier of analyzing massive amounts of data, whether in a static database or streaming through a system. Data at that scale-terabytes and petabytes-is increasingly common in science (e.g., particle physics, remote sensing, genomics), Internet commerce, business analytics, national security, communications, and elsewhere. The tools that work to infer knowledge from data at smaller scales do not necessarily work, or work well, at such massive scale. New tools, skills, and approaches are necessary, and this report identifies many of them, plus promising research directions to explore. Frontiers in Massive Data Analysis discusses pitfalls in trying to infer knowledge from massive data, and it characterizes seven major classes of computation that are common in the analysis of massive data. Overall, this report illustrates the cross-disciplinary knowledge-from computer science, statistics, machine learning, and application disciplines-that must be brought to bear to make useful inferences from massive data.

Optimization

Author : Jean-Bapiste Hiriart-Urruty
Publisher : CRC Press
ISBN 13 : 1000110516
Total Pages : 272 pages
Book Rating : 4.0/5 (1 download)

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Book Synopsis Optimization by : Jean-Bapiste Hiriart-Urruty

Download or read book Optimization written by Jean-Bapiste Hiriart-Urruty and published by CRC Press. This book was released on 2020-11-25 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is concerned with tangent cones, duality formulas, a generalized concept of conjugation, and the notion of maxi-minimizing sequence for a saddle-point problem, and deals more with algorithms in optimization. It focuses on the multiple exchange algorithm in convex programming.