Download or read book M thodes d apprentissage statistique pour la r gression et l optimisation globale de mesures de risque written by Léonard Torossian and published by . This book was released on 2019 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cette thèse s'inscrit dans le contexte général de l'estimation et de l'optimisation de fonctions de type boîte noire dont la sortie est une variable aléatoire. Motivé par la nécessité de quantifier l'occurrence d'événements extrêmes dans des disciplines comme la médecine, l'agriculture ou la finance, dans cette thèse des indicateurs sur certaines propriétés de la distribution en sortie, comme la variance ou la taille des queues de dis- tribution, sont étudiés. De nombreux indicateurs, aussi connus sous le nom de mesure de risque, ont été proposés dans la littérature ces dernières années. Dans cette thèse nous concentrons notre intérêt sur les quantiles, CVaR et expectiles. Dans un premier temps, nous comparons les approches K-plus proches voisins, forêts aléatoires, régression dans les RKHS, régression par réseaux de neurones et régression par processus gaussiens pour l'estimation d'un quantile conditionnel d'une fonction boite noire. Puis, nous proposons l'utilisation d'un modèle de régression basé sur le couplage de deux processus gaussiens estimés par une méthode variationnelle. Nous montrons que ce modèle, ini- tialement développé pour la régression quantile, est facilement adaptable à la régression d'autres mesures de risque. Nous l'illustrons avec l'expectile. Dans un second temps, nous analysons le problème relatif à l'optimisation d'une mesure de risque. Nous proposons une approche générique inspirée de la littérature X-armed bandits, permettantde fournir un algorithme d'optimisation, ainsi qu'une borne supérieure sur le regret, adaptable au choix de la mesure de risque. L'applicabilité de cette approche est illustrée par l'optimisation d'un quantile ou d'une CVaR. Enfin, nous proposons des algorithmes d'optimisation utilisant des processus gaussiens associés aux stratégies UCB et Thompson sampling, notre objectif étant l'optimisation d'un quantile ou d'un expectile.
Download or read book Life Insurance Mathematics written by Hans U. Gerber and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 137 pages. Available in PDF, EPUB and Kindle. Book excerpt: HaIley's Comet has been prominently displayed in many newspapers during the last few months. For the first time in 76 years it appeared this winter, clearly visible against the nocturnal sky. This is an appropriate occasion to point out the fact that Sir Edmund Halley also constructed the world's first life table in 1693, thus creating the scientific foundation of life insurance. Halley's life table and its successors were viewed as deterministic laws, i. e. the number of deaths in any given group and year was considered to be a weIl defined number that could be calculated by means of a life table. However, in reality this number is random. Thus any mathematical treatment of life insurance will have to rely more and more on prob ability theory. By sponsoring this monograph the Swiss Association of Actuaries wishes to support the "modern" probabilistic view oflife contingencies. We are fortu nate that Professor Gerber, an internationally renowned expert, has assumed the task of writing the monograph. We thank the Springer-Verlag and hope that this monograph will be the first in a successful series of actuarial texts. Hans Bühlmann Zürich, March 1986 President Swiss Association of Actuaries Preface Two major developments have influenced the environment of actuarial math ematics. One is the arrival of powerful and affordable computers; the once important problem of numerical calculation has become almost trivial in many instances.
Download or read book Predicting Structured Data written by Neural Information Processing Systems Foundation and published by MIT Press. This book was released on 2007 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: State-of-the-art algorithms and theory in a novel domain of machine learning, prediction when the output has structure.
Download or read book Statistical Inference for Ergodic Diffusion Processes written by Yury A. Kutoyants and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 493 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first book in inference for stochastic processes from a statistical, rather than a probabilistic, perspective. It provides a systematic exposition of theoretical results from over ten years of mathematical literature and presents, for the first time in book form, many new techniques and approaches.
Download or read book Semiparametric Theory and Missing Data written by Anastasios Tsiatis and published by Springer Science & Business Media. This book was released on 2007-01-15 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book summarizes current knowledge regarding the theory of estimation for semiparametric models with missing data, in an organized and comprehensive manner. It starts with the study of semiparametric methods when there are no missing data. The description of the theory of estimation for semiparametric models is both rigorous and intuitive, relying on geometric ideas to reinforce the intuition and understanding of the theory. These methods are then applied to problems with missing, censored, and coarsened data with the goal of deriving estimators that are as robust and efficient as possible.
Download or read book An Introduction to Computational Learning Theory written by Michael J. Kearns and published by MIT Press. This book was released on 1994-08-15 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: Emphasizing issues of computational efficiency, Michael Kearns and Umesh Vazirani introduce a number of central topics in computational learning theory for researchers and students in artificial intelligence, neural networks, theoretical computer science, and statistics. Emphasizing issues of computational efficiency, Michael Kearns and Umesh Vazirani introduce a number of central topics in computational learning theory for researchers and students in artificial intelligence, neural networks, theoretical computer science, and statistics. Computational learning theory is a new and rapidly expanding area of research that examines formal models of induction with the goals of discovering the common methods underlying efficient learning algorithms and identifying the computational impediments to learning. Each topic in the book has been chosen to elucidate a general principle, which is explored in a precise formal setting. Intuition has been emphasized in the presentation to make the material accessible to the nontheoretician while still providing precise arguments for the specialist. This balance is the result of new proofs of established theorems, and new presentations of the standard proofs. The topics covered include the motivation, definitions, and fundamental results, both positive and negative, for the widely studied L. G. Valiant model of Probably Approximately Correct Learning; Occam's Razor, which formalizes a relationship between learning and data compression; the Vapnik-Chervonenkis dimension; the equivalence of weak and strong learning; efficient learning in the presence of noise by the method of statistical queries; relationships between learning and cryptography, and the resulting computational limitations on efficient learning; reducibility between learning problems; and algorithms for learning finite automata from active experimentation.
Download or read book The Nature of Statistical Learning Theory written by Vladimir Vapnik and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this book is to discuss the fundamental ideas which lie behind the statistical theory of learning and generalization. It considers learning as a general problem of function estimation based on empirical data. Omitting proofs and technical details, the author concentrates on discussing the main results of learning theory and their connections to fundamental problems in statistics. This second edition contains three new chapters devoted to further development of the learning theory and SVM techniques. Written in a readable and concise style, the book is intended for statisticians, mathematicians, physicists, and computer scientists.
Download or read book Medical Image Computing and Computer Assisted Intervention MICCAI 2012 written by Nicholas Ayache and published by Springer. This book was released on 2012-08-28 with total page 645 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three-volume set LNCS 7510, 7511, and 7512 constitutes the refereed proceedings of the 15th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2012, held in Nice, France, in October 2012. Based on rigorous peer reviews, the program committee carefully selected 252 revised papers from 781 submissions for presentation in three volumes. The third volume includes 79 papers organized in topical sections on diffusion imaging: from acquisition to tractography; image acquisition, segmentation and recognition; image registration; neuroimage analysis; analysis of microscopic and optical images; image segmentation; diffusion weighted imaging; computer-aided diagnosis and planning; and microscopic image analysis.
Download or read book Flight Vehicle System Identification written by Ravindra V. Jategaonkar and published by AIAA (American Institute of Aeronautics & Astronautics). This book was released on 2006 with total page 568 pages. Available in PDF, EPUB and Kindle. Book excerpt: This valuable volume offers a systematic approach to flight vehicle system identification and exhaustively covers the time domain methodology. It addresses in detail the theoretical and practical aspects of various parameter estimation methods, including those in the stochastic framework and focusing on nonlinear models, cost functions, optimization methods, and residual analysis. A pragmatic and balanced account of pros and cons in each case is provided. The book also presents data gathering and model validation, and covers both large-scale systems and high-fidelity modeling. Real world problems dealing with a variety of flight vehicle applications are addressed and solutions are provided. Examples encompass such problems as estimation of aerodynamics, stability, and control derivatives from flight data, flight path reconstruction, nonlinearities in control surface effectiveness, stall hysteresis, unstable aircraft, and other critical considerations.
Download or read book Reinforcement Learning second edition written by Richard S. Sutton and published by MIT Press. This book was released on 2018-11-13 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics. Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. Part III has new chapters on reinforcement learning's relationships to psychology and neuroscience, as well as an updated case-studies chapter including AlphaGo and AlphaGo Zero, Atari game playing, and IBM Watson's wagering strategy. The final chapter discusses the future societal impacts of reinforcement learning.
Download or read book Multistage Stochastic Optimization written by Georg Ch. Pflug and published by Springer. This book was released on 2014-11-12 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multistage stochastic optimization problems appear in many ways in finance, insurance, energy production and trading, logistics and transportation, among other areas. They describe decision situations under uncertainty and with a longer planning horizon. This book contains a comprehensive treatment of today’s state of the art in multistage stochastic optimization. It covers the mathematical backgrounds of approximation theory as well as numerous practical algorithms and examples for the generation and handling of scenario trees. A special emphasis is put on estimation and bounding of the modeling error using novel distance concepts, on time consistency and the role of model ambiguity in the decision process. An extensive treatment of examples from electricity production, asset liability management and inventory control concludes the book.
Download or read book The Generic Chaining written by Michel Talagrand and published by Springer Science & Business Media. This book was released on 2005-12-08 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fundamental question of characterizing continuity and boundedness of Gaussian processes goes back to Kolmogorov. After contributions by R. Dudley and X. Fernique, it was solved by the author. This book provides an overview of "generic chaining", a completely natural variation on the ideas of Kolmogorov. It takes the reader from the first principles to the edge of current knowledge and to the open problems that remain in this domain.
Download or read book Parliamentary Oversight of the Security Sector written by Philipp Fluri and published by DCAF. This book was released on 2003 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Efficient R Programming written by Colin Gillespie and published by "O'Reilly Media, Inc.". This book was released on 2016-12-08 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: There are many excellent R resources for visualization, data science, and package development. Hundreds of scattered vignettes, web pages, and forums explain how to use R in particular domains. But little has been written on how to simply make R work effectively—until now. This hands-on book teaches novices and experienced R users how to write efficient R code. Drawing on years of experience teaching R courses, authors Colin Gillespie and Robin Lovelace provide practical advice on a range of topics—from optimizing the set-up of RStudio to leveraging C++—that make this book a useful addition to any R user’s bookshelf. Academics, business users, and programmers from a wide range of backgrounds stand to benefit from the guidance in Efficient R Programming. Get advice for setting up an R programming environment Explore general programming concepts and R coding techniques Understand the ingredients of an efficient R workflow Learn how to efficiently read and write data in R Dive into data carpentry—the vital skill for cleaning raw data Optimize your code with profiling, standard tricks, and other methods Determine your hardware capabilities for handling R computation Maximize the benefits of collaborative R programming Accelerate your transition from R hacker to R programmer
Download or read book Transformative Learning and Teaching in Physical Education written by Malcolm Thorburn and published by Taylor & Francis. This book was released on 2017-04-07 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: Transformative Learning and Teaching in Physical Education explores how learning and teaching in physical education might be improved and how it might become a meaningful component of young people’s lives. With its in-depth focus on physical education within contemporary schooling, the book presents a set of professional perspectives that are pivotal for realising high-quality learning and teaching for physical education. With contributions from a range of international academics, chapters critically engage with vital issues within contemporary physical education. These include examples of complex learning principles in action, which are discussed as a method for bettering our understanding of various learning and teaching endeavours, and which often challenge hierarchical and behaviourist notions of learning that have long held a strong foothold in physical education. Authors also engage with social-ecological theories in order to help probe the complex circumstances and tensions which many teachers face in their everyday work environments, where they witness first-hand the contrast between discourses which espouse transformational change and the realities of their routine institutional arrangements. This book enables readers to engage in a fuller way with transformative ideas and to consider their wider implications for contemporary physical education. Its set of professional perspectives will be of great interest to academics, policymakers, teacher educators and teachers in the fields of physical education, health and well-being. It will also be a useful resource for postgraduate students studying in these subject areas.
Download or read book Product Life Cycle Management written by Max Giordano and published by John Wiley & Sons. This book was released on 2012-12-17 with total page 389 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gives a comprehensive view of the most recent major international research in the field of tolerancing, and is an excellent resource for anyone interested in Computer Aided Tolerating. It is organized into 4 parts. Part 1 focuses on the more general problems of tolerance analysis and synthesis, for tolerancing in mechanical design and manufacturing processes. Part 2 specifically highlights the simulation of assembly with defects, and the influence of tolerances on the quality of the assembly. Part 3 deals with measurement aspects, and quality control throughout the life cycle. Different measurement technologies and methods for estimating uncertainty are considered. In Part 4, different aspects of tolerancing and their interactions are explored, from the definition of functional requirement to measurement processes in a PLM approach.
Download or read book Medical image computing and computer assisted intervention written by Nicholas Ayache and published by . This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
