Some Optimization Problems In 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.

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:

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.

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.

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.

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.

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.

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.

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.

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.

Optimization for Industrial Problems

Author : Patrick Bangert
Publisher : Springer Science & Business Media
ISBN 13 : 3642249744
Total Pages : 264 pages
Book Rating : 4.6/5 (422 download)

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Book Synopsis Optimization for Industrial Problems by : Patrick Bangert

Download or read book Optimization for Industrial Problems written by Patrick Bangert and published by Springer Science & Business Media. This book was released on 2012-01-05 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: Industrial optimization lies on the crossroads between mathematics, computer science, engineering and management. This book presents these fields in interdependence as a conversation between theoretical aspects of mathematics and computer science and the mathematical field of optimization theory at a practical level. The 19 case studies that were conducted by the author in real enterprises in cooperation and co-authorship with some of the leading industrial enterprises, including RWE, Vattenfall, EDF, PetroChina, Vestolit, Sasol, and Hella, illustrate the results that may be reasonably expected from an optimization project in a commercial enterprise. The book is aimed at persons working in industrial facilities as managers or engineers; it is also suitable for university students and their professors as an illustration of how the academic material may be used in real life. It will not make its reader a mathematician but it will help its reader in improving his plant.

Computational Intelligence in Expensive Optimization Problems

Author : Yoel Tenne
Publisher : Springer Science & Business Media
ISBN 13 : 364210701X
Total Pages : 736 pages
Book Rating : 4.6/5 (421 download)

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Book Synopsis Computational Intelligence in Expensive Optimization Problems by : Yoel Tenne

Download or read book Computational Intelligence in Expensive Optimization Problems written by Yoel Tenne and published by Springer Science & Business Media. This book was released on 2010-03-10 with total page 736 pages. Available in PDF, EPUB and Kindle. Book excerpt: In modern science and engineering, laboratory experiments are replaced by high fidelity and computationally expensive simulations. Using such simulations reduces costs and shortens development times but introduces new challenges to design optimization process. Examples of such challenges include limited computational resource for simulation runs, complicated response surface of the simulation inputs-outputs, and etc. Under such difficulties, classical optimization and analysis methods may perform poorly. This motivates the application of computational intelligence methods such as evolutionary algorithms, neural networks and fuzzy logic, which often perform well in such settings. This is the first book to introduce the emerging field of computational intelligence in expensive optimization problems. Topics covered include: dedicated implementations of evolutionary algorithms, neural networks and fuzzy logic. reduction of expensive evaluations (modelling, variable-fidelity, fitness inheritance), frameworks for optimization (model management, complexity control, model selection), parallelization of algorithms (implementation issues on clusters, grids, parallel machines), incorporation of expert systems and human-system interface, single and multiobjective algorithms, data mining and statistical analysis, analysis of real-world cases (such as multidisciplinary design optimization). The edited book provides both theoretical treatments and real-world insights gained by experience, all contributed by leading researchers in the respective fields. As such, it is a comprehensive reference for researchers, practitioners, and advanced-level students interested in both the theory and practice of using computational intelligence for expensive optimization problems.

Optimization Models

Author : Giuseppe C. Calafiore
Publisher : Cambridge University Press
ISBN 13 : 1107050871
Total Pages : 651 pages
Book Rating : 4.1/5 (7 download)

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Book Synopsis Optimization Models by : Giuseppe C. Calafiore

Download or read book Optimization Models written by Giuseppe C. Calafiore and published by Cambridge University Press. This book was released on 2014-10-31 with total page 651 pages. Available in PDF, EPUB and Kindle. Book excerpt: This accessible textbook demonstrates how to recognize, simplify, model and solve optimization problems - and apply these principles to new projects.

Branch-and-Bound Applications in Combinatorial Data Analysis

Author : Michael J. Brusco
Publisher : Springer Science & Business Media
ISBN 13 : 0387288104
Total Pages : 222 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Branch-and-Bound Applications in Combinatorial Data Analysis by : Michael J. Brusco

Download or read book Branch-and-Bound Applications in Combinatorial Data Analysis written by Michael J. Brusco and published by Springer Science & Business Media. This book was released on 2005-11-30 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides clear explanatory text, illustrative mathematics and algorithms, demonstrations of the iterative process, pseudocode, and well-developed examples for applications of the branch-and-bound paradigm to important problems in combinatorial data analysis. Supplementary material, such as computer programs, are provided on the world wide web. Dr. Brusco is an editorial board member for the Journal of Classification, and a member of the Board of Directors for the Classification Society of North America.

Numerical Optimization

Author : Jorge Nocedal
Publisher : Springer Science & Business Media
ISBN 13 : 0387400656
Total Pages : 686 pages
Book Rating : 4.3/5 (874 download)

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Book Synopsis Numerical Optimization by : Jorge Nocedal

Download or read book Numerical Optimization written by Jorge Nocedal and published by Springer Science & Business Media. This book was released on 2006-12-11 with total page 686 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimization is an important tool used in decision science and for the analysis of physical systems used in engineering. One can trace its roots to the Calculus of Variations and the work of Euler and Lagrange. This natural and reasonable approach to mathematical programming covers numerical methods for finite-dimensional optimization problems. It begins with very simple ideas progressing through more complicated concepts, concentrating on methods for both unconstrained and constrained optimization.

Python for Algorithmic Trading

Author : Yves Hilpisch
Publisher : O'Reilly Media
ISBN 13 : 1492053325
Total Pages : 380 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Python for Algorithmic Trading by : Yves Hilpisch

Download or read book Python for Algorithmic Trading written by Yves Hilpisch and published by O'Reilly Media. This book was released on 2020-11-12 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: Algorithmic trading, once the exclusive domain of institutional players, is now open to small organizations and individual traders using online platforms. The tool of choice for many traders today is Python and its ecosystem of powerful packages. In this practical book, author Yves Hilpisch shows students, academics, and practitioners how to use Python in the fascinating field of algorithmic trading. You'll learn several ways to apply Python to different aspects of algorithmic trading, such as backtesting trading strategies and interacting with online trading platforms. Some of the biggest buy- and sell-side institutions make heavy use of Python. By exploring options for systematically building and deploying automated algorithmic trading strategies, this book will help you level the playing field. Set up a proper Python environment for algorithmic trading Learn how to retrieve financial data from public and proprietary data sources Explore vectorization for financial analytics with NumPy and pandas Master vectorized backtesting of different algorithmic trading strategies Generate market predictions by using machine learning and deep learning Tackle real-time processing of streaming data with socket programming tools Implement automated algorithmic trading strategies with the OANDA and FXCM trading platforms