EBookClubs

Read Books & Download eBooks Full Online

EBookClubs

Read Books & Download eBooks Full Online

Book A risk gain sparsity optimization approach

Download or read book A risk gain sparsity optimization approach written by Alessandra Congedo and published by Roma TrE-Press. This book was released on 2024-06-12 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uno dei principi fondamentali dei modelli di selezione del portafoglio è la minimizzazione del rischio attraverso la diversificazione degli investimenti. Tuttavia, i benefici della diversificazione si riducono in presenza di un'elevata correlazione tra gli asset. È noto che la diversificazione attraverso l'uso di portafogli più ampi non è il modo migliore per ottenere un miglioramento della performance fuori campione. Inoltre, l'inclusione di un numero elevato di posizioni nel portafoglio aumenta i costi di gestione e di transazione. Mentre i modelli classici di selezione del portafoglio si concentrano sulla minimizzazione del rischio e sulla massimizzazione del rendimento, lo scopo di questo lavoro è quello di includere un terzo obiettivo: la norma-1. Ciò consente di selezionare portafogli sparsi, cioè con un numero limitato di attività, che sono più facili da gestire e consentono di ottenere buoni risultati in termini di rischio-rendimento. La nostra analisi empirica si basa su un dataset di riferimento disponibile pubblicamente e spesso utilizzato in letteratura. DOI: 10.13134/979-12-5977-332-6

Book Tree Based Methods for Statistical Learning in R

Download or read book Tree Based Methods for Statistical Learning in R written by Brandon M. Greenwell and published by CRC Press. This book was released on 2022-06-23 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: Tree-based Methods for Statistical Learning in R provides a thorough introduction to both individual decision tree algorithms (Part I) and ensembles thereof (Part II). Part I of the book brings several different tree algorithms into focus, both conventional and contemporary. Building a strong foundation for how individual decision trees work will help readers better understand tree-based ensembles at a deeper level, which lie at the cutting edge of modern statistical and machine learning methodology. The book follows up most ideas and mathematical concepts with code-based examples in the R statistical language; with an emphasis on using as few external packages as possible. For example, users will be exposed to writing their own random forest and gradient tree boosting functions using simple for loops and basic tree fitting software (like rpart and party/partykit), and more. The core chapters also end with a detailed section on relevant software in both R and other opensource alternatives (e.g., Python, Spark, and Julia), and example usage on real data sets. While the book mostly uses R, it is meant to be equally accessible and useful to non-R programmers. Consumers of this book will have gained a solid foundation (and appreciation) for tree-based methods and how they can be used to solve practical problems and challenges data scientists often face in applied work. Features: Thorough coverage, from the ground up, of tree-based methods (e.g., CART, conditional inference trees, bagging, boosting, and random forests). A companion website containing additional supplementary material and the code to reproduce every example and figure in the book. A companion R package, called treemisc, which contains several data sets and functions used throughout the book (e.g., there’s an implementation of gradient tree boosting with LAD loss that shows how to perform the line search step by updating the terminal node estimates of a fitted rpart tree). Interesting examples that are of practical use; for example, how to construct partial dependence plots from a fitted model in Spark MLlib (using only Spark operations), or post-processing tree ensembles via the LASSO to reduce the number of trees while maintaining, or even improving performance.

Book Bridge Maintenance  Safety  Management  Life Cycle Sustainability and Innovations

Download or read book Bridge Maintenance Safety Management Life Cycle Sustainability and Innovations written by Hiroshi Yokota and published by CRC Press. This book was released on 2021-04-20 with total page 926 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bridge Maintenance, Safety, Management, Life-Cycle Sustainability and Innovations contains lectures and papers presented at the Tenth International Conference on Bridge Maintenance, Safety and Management (IABMAS 2020), held in Sapporo, Hokkaido, Japan, April 11–15, 2021. This volume consists of a book of extended abstracts and a USB card containing the full papers of 571 contributions presented at IABMAS 2020, including the T.Y. Lin Lecture, 9 Keynote Lectures, and 561 technical papers from 40 countries. The contributions presented at IABMAS 2020 deal with the state of the art as well as emerging concepts and innovative applications related to the main aspects of maintenance, safety, management, life-cycle sustainability and technological innovations of bridges. Major topics include: advanced bridge design, construction and maintenance approaches, safety, reliability and risk evaluation, life-cycle management, life-cycle sustainability, standardization, analytical models, bridge management systems, service life prediction, maintenance and management strategies, structural health monitoring, non-destructive testing and field testing, safety, resilience, robustness and redundancy, durability enhancement, repair and rehabilitation, fatigue and corrosion, extreme loads, and application of information and computer technology and artificial intelligence for bridges, among others. This volume provides both an up-to-date overview of the field of bridge engineering and significant contributions to the process of making more rational decisions on maintenance, safety, management, life-cycle sustainability and technological innovations of bridges for the purpose of enhancing the welfare of society. The Editors hope that these Proceedings will serve as a valuable reference to all concerned with bridge structure and infrastructure systems, including engineers, researchers, academics and students from all areas of bridge engineering.

Book Distributed Optimization and Statistical Learning Via the Alternating Direction Method of Multipliers

Download or read book Distributed Optimization and Statistical Learning Via the Alternating Direction Method of Multipliers written by Stephen Boyd and published by Now Publishers Inc. This book was released on 2011 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: Surveys the theory and history of the alternating direction method of multipliers, and discusses its applications to a wide variety of statistical and machine learning problems of recent interest, including the lasso, sparse logistic regression, basis pursuit, covariance selection, support vector machines, and many others.

Book Advances in Cooperative Control and Optimization

Download or read book Advances in Cooperative Control and Optimization written by Michael Hirsch and published by Springer Science & Business Media. This book was released on 2007-09-20 with total page 422 pages. Available in PDF, EPUB and Kindle. Book excerpt: Across the globe, the past several years have seen a tremendous increase in the role of cooperative autonomous systems. The field of cooperative control and optimization has established itself as a part of many different scientific disciplines. The contents of this hugely important volume, which adds much to the debate on the subject, are culled from papers presented at the Seventh Annual International Conference on Cooperative Control and Optimization, held in Gainesville, Florida, in January 2007.

Book Metaheuristics

    Book Details:
  • Author : Marc Sevaux
  • Publisher : Springer Nature
  • Release :
  • ISBN : 3031629221
  • Pages : 414 pages

Download or read book Metaheuristics written by Marc Sevaux and published by Springer Nature. This book was released on with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Optimization Models

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.

Book Optimization Methods in Finance

Download or read book Optimization Methods in Finance written by Gerard Cornuejols and published by Cambridge University Press. This book was released on 2006-12-21 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimization models play an increasingly important role in financial decisions. This is the first textbook devoted to explaining how recent advances in optimization models, methods and software can be applied to solve problems in computational finance more efficiently and accurately. Chapters discussing the theory and efficient solution methods for all major classes of optimization problems alternate with chapters illustrating their use in modeling problems of mathematical finance. The reader is guided through topics such as volatility estimation, portfolio optimization problems and constructing an index fund, using techniques such as nonlinear optimization models, quadratic programming formulations and integer programming models respectively. The book is based on Master's courses in financial engineering and comes with worked examples, exercises and case studies. It will be welcomed by applied mathematicians, operational researchers and others who work in mathematical and computational finance and who are seeking a text for self-learning or for use with courses.

Book Encyclopedia of Optimization

Download or read book Encyclopedia of Optimization written by Christodoulos A. Floudas and published by Springer Science & Business Media. This book was released on 2008-09-04 with total page 4646 pages. Available in PDF, EPUB and Kindle. Book excerpt: The goal of the Encyclopedia of Optimization is to introduce the reader to a complete set of topics that show the spectrum of research, the richness of ideas, and the breadth of applications that has come from this field. The second edition builds on the success of the former edition with more than 150 completely new entries, designed to ensure that the reference addresses recent areas where optimization theories and techniques have advanced. Particularly heavy attention resulted in health science and transportation, with entries such as "Algorithms for Genomics", "Optimization and Radiotherapy Treatment Design", and "Crew Scheduling".

Book Statistical Learning with Sparsity

Download or read book Statistical Learning with Sparsity written by Trevor Hastie and published by CRC Press. This book was released on 2015-05-07 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover New Methods for Dealing with High-Dimensional DataA sparse statistical model has only a small number of nonzero parameters or weights; therefore, it is much easier to estimate and interpret than a dense model. Statistical Learning with Sparsity: The Lasso and Generalizations presents methods that exploit sparsity to help recover the underl

Book Advances in Visual Computing

Download or read book Advances in Visual Computing written by George Bebis and published by Springer. This book was released on 2012-08-22 with total page 769 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two volume set LNCS 7431 and 7432 constitutes the refereed proceedings of the 8th International Symposium on Visual Computing, ISVC 2012, held in Rethymnon, Crete, Greece, in July 2012. The 68 revised full papers and 35 poster papers presented together with 45 special track papers were carefully reviewed and selected from more than 200 submissions. The papers are organized in topical sections: Part I (LNCS 7431) comprises computational bioimaging; computer graphics; calibration and 3D vision; object recognition; illumination, modeling, and segmentation; visualization; 3D mapping, modeling and surface reconstruction; motion and tracking; optimization for vision, graphics, and medical imaging, HCI and recognition. Part II (LNCS 7432) comprises topics such as unconstrained biometrics: advances and trends; intelligent environments: algorithms and applications; applications; virtual reality; face processing and recognition.

Book Data Science in Engineering  Volume 9

Download or read book Data Science in Engineering Volume 9 written by Ramin Madarshahian and published by Springer Nature. This book was released on 2021-10-04 with total page 287 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Science and Engineering Volume 9: Proceedings of the 39th IMAC, A Conference and Exposition on Structural Dynamics, 2021, the ninth volume of nine from the Conference, brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Data Science in Engineering, including papers on: Data Science in Engineering Applications Engineering Mathematics Computational Methods in Engineering

Book Classification Methods for High dimensional Sparse Data

Download or read book Classification Methods for High dimensional Sparse Data written by Tao Xiong and published by . This book was released on 2007 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Machine Learning and Knowledge Discovery in Databases

Download or read book Machine Learning and Knowledge Discovery in Databases written by Toon Calders and published by Springer. This book was released on 2014-09-01 with total page 749 pages. Available in PDF, EPUB and Kindle. Book excerpt: This three-volume set LNAI 8724, 8725 and 8726 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2014, held in Nancy, France, in September 2014. The 115 revised research papers presented together with 13 demo track papers, 10 nectar track papers, 8 PhD track papers, and 9 invited talks were carefully reviewed and selected from 550 submissions. The papers cover the latest high-quality interdisciplinary research results in all areas related to machine learning and knowledge discovery in databases.

Book Spectral Theory of Large Dimensional Random Matrices and Its Applications to Wireless Communications and Finance Statistics

Download or read book Spectral Theory of Large Dimensional Random Matrices and Its Applications to Wireless Communications and Finance Statistics written by Zhidong Bai and published by World Scientific. This book was released on 2014-01-24 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book contains three parts: Spectral theory of large dimensional random matrices; Applications to wireless communications; and Applications to finance. In the first part, we introduce some basic theorems of spectral analysis of large dimensional random matrices that are obtained under finite moment conditions, such as the limiting spectral distributions of Wigner matrix and that of large dimensional sample covariance matrix, limits of extreme eigenvalues, and the central limit theorems for linear spectral statistics. In the second part, we introduce some basic examples of applications of random matrix theory to wireless communications and in the third part, we present some examples of Applications to statistical finance. Contents:IntroductionLimiting Spectral DistributionsExtreme EigenvaluesCentral Limit Theorems of Linear Spectral StatisticsLimiting Behavior of Eigenmatrix of Sample Covariance MatrixWireless CommunicationsLimiting Performances of Linear and Iterative ReceiversApplication to Finance Readership: Graduate students and researchers in random matrices. Key Features:The book introduces basic theorems in large dimensional random matrices emphasizing those which are established under moment conditions and are thus applicable to statisticsThe long proofs of some theorems are omitted and their references have been providedExamples of various applications to wireless communications and finance are givenKeywords:Statistical Finance;Random Matrix Theory;Spectral Analysis of Random Matrices;Wireless CommunicationsReviews: “Practitioners looking for an introduction to the applications of random matrix theory to finance will find this part useful.” Mathematical Reviews Clippings

Book Progress in Advanced Computing and Intelligent Engineering

Download or read book Progress in Advanced Computing and Intelligent Engineering written by Khalid Saeed and published by Springer. This book was released on 2017-12-21 with total page 723 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book focuses on both theory and applications in the broad areas of communication technology, computer science and information security. This two volume book contains the Proceedings of International Conference on Advanced Computing and Intelligent Engineering. These volumes bring together academic scientists, professors, research scholars and students to share and disseminate information on knowledge and scientific research works related to computing, networking, and informatics to discuss the practical challenges encountered and the solutions adopted. The book also promotes translation of basic research into applied investigation and convert applied investigation into practice.

Book Financial Risk Modelling and Portfolio Optimization with R

Download or read book Financial Risk Modelling and Portfolio Optimization with R written by Bernhard Pfaff and published by John Wiley & Sons. This book was released on 2016-08-16 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: Financial Risk Modelling and Portfolio Optimization with R, 2nd Edition Bernhard Pfaff, Invesco Global Asset Allocation, Germany A must have text for risk modelling and portfolio optimization using R. This book introduces the latest techniques advocated for measuring financial market risk and portfolio optimization, and provides a plethora of R code examples that enable the reader to replicate the results featured throughout the book. This edition has been extensively revised to include new topics on risk surfaces and probabilistic utility optimization as well as an extended introduction to R language. Financial Risk Modelling and Portfolio Optimization with R: Demonstrates techniques in modelling financial risks and applying portfolio optimization techniques as well as recent advances in the field. Introduces stylized facts, loss function and risk measures, conditional and unconditional modelling of risk; extreme value theory, generalized hyperbolic distribution, volatility modelling and concepts for capturing dependencies. Explores portfolio risk concepts and optimization with risk constraints. Is accompanied by a supporting website featuring examples and case studies in R. Includes updated list of R packages for enabling the reader to replicate the results in the book. Graduate and postgraduate students in finance, economics, risk management as well as practitioners in finance and portfolio optimization will find this book beneficial. It also serves well as an accompanying text in computer-lab classes and is therefore suitable for self-study.