Estimation And Testing Under Sparsity

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Estimation and Testing Under Sparsity

Author : Sara van de Geer
Publisher : Springer
ISBN 13 : 3319327747
Total Pages : 278 pages
Book Rating : 4.3/5 (193 download)

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Book Synopsis Estimation and Testing Under Sparsity by : Sara van de Geer

Download or read book Estimation and Testing Under Sparsity written by Sara van de Geer and published by Springer. This book was released on 2016-06-28 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: Taking the Lasso method as its starting point, this book describes the main ingredients needed to study general loss functions and sparsity-inducing regularizers. It also provides a semi-parametric approach to establishing confidence intervals and tests. Sparsity-inducing methods have proven to be very useful in the analysis of high-dimensional data. Examples include the Lasso and group Lasso methods, and the least squares method with other norm-penalties, such as the nuclear norm. The illustrations provided include generalized linear models, density estimation, matrix completion and sparse principal components. Each chapter ends with a problem section. The book can be used as a textbook for a graduate or PhD course.

Sparsity Methods for Systems and Control

Author : Masaaki Nagahara
Publisher :
ISBN 13 : 9781680837247
Total Pages : 220 pages
Book Rating : 4.8/5 (372 download)

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Book Synopsis Sparsity Methods for Systems and Control by : Masaaki Nagahara

Download or read book Sparsity Methods for Systems and Control written by Masaaki Nagahara and published by . This book was released on 2020-09-30 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: The method of sparsity has been attracting a lot of attention in the fields related not only to signal processing, machine learning, and statistics, but also systems and control. The method is known as compressed sensing, compressive sampling, sparse representation, or sparse modeling. More recently, the sparsity method has been applied to systems and control to design resource-aware control systems. This book gives a comprehensive guide to sparsity methods for systems and control, from standard sparsity methods in finite-dimensional vector spaces (Part I) to optimal control methods in infinite-dimensional function spaces (Part II). The primary objective of this book is to show how to use sparsity methods for several engineering problems. For this, the author provides MATLAB programs by which the reader can try sparsity methods for themselves. Readers will obtain a deep understanding of sparsity methods by running these MATLAB programs. Sparsity Methods for Systems and Control is suitable for graduate level university courses, though it should also be comprehendible to undergraduate students who have a basic knowledge of linear algebra and elementary calculus. Also, especially part II of the book should appeal to professional researchers and engineers who are interested in applying sparsity methods to systems and control.

Algorithms and Computation

Author : Seok-Hee Hong
Publisher : Springer Science & Business Media
ISBN 13 : 3540921818
Total Pages : 962 pages
Book Rating : 4.5/5 (49 download)

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Book Synopsis Algorithms and Computation by : Seok-Hee Hong

Download or read book Algorithms and Computation written by Seok-Hee Hong and published by Springer Science & Business Media. This book was released on 2008-12 with total page 962 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 19th International Symposium on Algorithms and Computation, ISAAC 2008, held in Gold Coast, Australia in December 2008. The 78 revised full papers together with 3 invited talks presented were carefully reviewed and selected from 229 submissions for inclusion in the book. The papers are organized in topical sections on approximation algorithms, online algorithms, data structure and algorithms, game theory, graph algorithms, fixed parameter tractability, distributed algorithms, database, approximation algorithms, computational biology, computational geometry, complexity, networks, optimization as well as routing.

Proceedings of the Pacific Rim Statistical Conference for Production Engineering

Author : Dongseok Choi
Publisher : Springer
ISBN 13 : 9811081689
Total Pages : 168 pages
Book Rating : 4.8/5 (11 download)

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Book Synopsis Proceedings of the Pacific Rim Statistical Conference for Production Engineering by : Dongseok Choi

Download or read book Proceedings of the Pacific Rim Statistical Conference for Production Engineering written by Dongseok Choi and published by Springer. This book was released on 2018-03-27 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the proceedings of the 2nd Pacific Rim Statistical Conference for Production Engineering: Production Engineering, Big Data and Statistics, which took place at Seoul National University in Seoul, Korea in December, 2016. The papers included discuss a wide range of statistical challenges, methods and applications for big data in production engineering, and introduce recent advances in relevant statistical methods.

Concentration of Maxima and Fundamental Limits in High-Dimensional Testing and Inference

Author : Zheng Gao
Publisher : Springer Nature
ISBN 13 : 3030809641
Total Pages : 147 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Concentration of Maxima and Fundamental Limits in High-Dimensional Testing and Inference by : Zheng Gao

Download or read book Concentration of Maxima and Fundamental Limits in High-Dimensional Testing and Inference written by Zheng Gao and published by Springer Nature. This book was released on 2021-09-07 with total page 147 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a unified exposition of some fundamental theoretical problems in high-dimensional statistics. It specifically considers the canonical problems of detection and support estimation for sparse signals observed with noise. Novel phase-transition results are obtained for the signal support estimation problem under a variety of statistical risks. Based on a surprising connection to a concentration of maxima probabilistic phenomenon, the authors obtain a complete characterization of the exact support recovery problem for thresholding estimators under dependent errors.

A Mixture Model Approach to Empirical Bayes Testing and Estimation

Author : Omkar Muralidharan
Publisher : Stanford University
ISBN 13 :
Total Pages : 89 pages
Book Rating : 4.F/5 ( download)

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Book Synopsis A Mixture Model Approach to Empirical Bayes Testing and Estimation by : Omkar Muralidharan

Download or read book A Mixture Model Approach to Empirical Bayes Testing and Estimation written by Omkar Muralidharan and published by Stanford University. This book was released on 2011 with total page 89 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many modern statistical problems require making similar decisions or estimates for many different entities. For example, we may ask whether each of 10,000 genes is associated with some disease, or try to measure the degree to which each is associated with the disease. As in this example, the entities can often be divided into a vast majority of "null" objects and a small minority of interesting ones. Empirical Bayes is a useful technique for such situations, but finding the right empirical Bayes method for each problem can be difficult. Mixture models, however, provide an easy and effective way to apply empirical Bayes. This thesis motivates mixture models by analyzing a simple high-dimensional problem, and shows their practical use by applying them to detecting single nucleotide polymorphisms.

Phenotypes and Genotypes

Author : Florian Frommlet
Publisher : Springer
ISBN 13 : 1447153103
Total Pages : 232 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Phenotypes and Genotypes by : Florian Frommlet

Download or read book Phenotypes and Genotypes written by Florian Frommlet and published by Springer. This book was released on 2016-02-12 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: This timely text presents a comprehensive guide to genetic association, a new and rapidly expanding field that aims to elucidate how our genetic code (genotypes) influences the traits we possess (phenotypes). The book provides a detailed review of methods of gene mapping used in association with experimental crosses, as well as genome-wide association studies. Emphasis is placed on model selection procedures for analyzing data from large-scale genome scans based on specifically designed modifications of the Bayesian information criterion. Features: presents a thorough introduction to the theoretical background to studies of genetic association (both genetic and statistical); reviews the latest advances in the field; illustrates the properties of methods for mapping quantitative trait loci using computer simulations and the analysis of real data; discusses open challenges; includes an extensive statistical appendix as a reference for those who are not totally familiar with the fundamentals of statistics.

Foundations of Modern Statistics

Author : Denis Belomestny
Publisher : Springer Nature
ISBN 13 : 3031301145
Total Pages : 603 pages
Book Rating : 4.0/5 (313 download)

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Book Synopsis Foundations of Modern Statistics by : Denis Belomestny

Download or read book Foundations of Modern Statistics written by Denis Belomestny and published by Springer Nature. This book was released on 2023-07-16 with total page 603 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains contributions from the participants of the international conference “Foundations of Modern Statistics” which took place at Weierstrass Institute for Applied Analysis and Stochastics (WIAS), Berlin, during November 6–8, 2019, and at Higher School of Economics (HSE University), Moscow, during November 30, 2019. The events were organized in honor of Professor Vladimir Spokoiny on the occasion of his 60th birthday. Vladimir Spokoiny has pioneered the field of adaptive statistical inference and contributed to a variety of its applications. His more than 30 years of research in the field of mathematical statistics had a great influence on the development of the mathematical theory of statistics to its present state. It has inspired many young researchers to start their research in this exciting field of mathematics. The papers contained in this book reflect the broad field of interests of Vladimir Spokoiny: optimal rates and non-asymptotic bounds in nonparametrics, Bayes approaches from a frequentist point of view, optimization, signal processing, and statistical theory motivated by models in applied fields. Materials prepared by famous scientists contain original scientific results, which makes the publication valuable for researchers working in these fields. The book concludes by a conversation of Vladimir Spokoiny with Markus Reiβ and Enno Mammen. This interview gives some background on the life of Vladimir Spokoiny and his many scientific interests and motivations.

Introduction to Nonparametric Estimation

Author : Alexandre B. Tsybakov
Publisher : Springer Science & Business Media
ISBN 13 : 0387790527
Total Pages : 222 pages
Book Rating : 4.3/5 (877 download)

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Book Synopsis Introduction to Nonparametric Estimation by : Alexandre B. Tsybakov

Download or read book Introduction to Nonparametric Estimation written by Alexandre B. Tsybakov and published by Springer Science & Business Media. This book was released on 2008-10-22 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: Developed from lecture notes and ready to be used for a course on the graduate level, this concise text aims to introduce the fundamental concepts of nonparametric estimation theory while maintaining the exposition suitable for a first approach in the field.

Sparse Graphical Modeling for High Dimensional Data

Author : Faming Liang
Publisher : CRC Press
ISBN 13 : 0429584806
Total Pages : 151 pages
Book Rating : 4.4/5 (295 download)

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Book Synopsis Sparse Graphical Modeling for High Dimensional Data by : Faming Liang

Download or read book Sparse Graphical Modeling for High Dimensional Data written by Faming Liang and published by CRC Press. This book was released on 2023-08-02 with total page 151 pages. Available in PDF, EPUB and Kindle. Book excerpt: A general framework for learning sparse graphical models with conditional independence tests Complete treatments for different types of data, Gaussian, Poisson, multinomial, and mixed data Unified treatments for data integration, network comparison, and covariate adjustment Unified treatments for missing data and heterogeneous data Efficient methods for joint estimation of multiple graphical models Effective methods of high-dimensional variable selection Effective methods of high-dimensional inference

Practical Applications of Sparse Modeling

Author : Irina Rish
Publisher : MIT Press
ISBN 13 : 0262325330
Total Pages : 265 pages
Book Rating : 4.2/5 (623 download)

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Book Synopsis Practical Applications of Sparse Modeling by : Irina Rish

Download or read book Practical Applications of Sparse Modeling written by Irina Rish and published by MIT Press. This book was released on 2014-09-19 with total page 265 pages. Available in PDF, EPUB and Kindle. Book excerpt: Key approaches in the rapidly developing area of sparse modeling, focusing on its application in fields including neuroscience, computational biology, and computer vision. Sparse modeling is a rapidly developing area at the intersection of statistical learning and signal processing, motivated by the age-old statistical problem of selecting a small number of predictive variables in high-dimensional datasets. This collection describes key approaches in sparse modeling, focusing on its applications in fields including neuroscience, computational biology, and computer vision. Sparse modeling methods can improve the interpretability of predictive models and aid efficient recovery of high-dimensional unobserved signals from a limited number of measurements. Yet despite significant advances in the field, a number of open issues remain when sparse modeling meets real-life applications. The book discusses a range of practical applications and state-of-the-art approaches for tackling the challenges presented by these applications. Topics considered include the choice of method in genomics applications; analysis of protein mass-spectrometry data; the stability of sparse models in brain imaging applications; sequential testing approaches; algorithmic aspects of sparse recovery; and learning sparse latent models. Contributors A. Vania Apkarian, Marwan Baliki, Melissa K. Carroll, Guillermo A. Cecchi, Volkan Cevher, Xi Chen, Nathan W. Churchill, Rémi Emonet, Rahul Garg, Zoubin Ghahramani, Lars Kai Hansen, Matthias Hein, Katherine Heller, Sina Jafarpour, Seyoung Kim, Mladen Kolar, Anastasios Kyrillidis, Seunghak Lee, Aurelie Lozano, Matthew L. Malloy, Pablo Meyer, Shakir Mohamed, Alexandru Niculescu-Mizil, Robert D. Nowak, Jean-Marc Odobez, Peter M. Rasmussen, Irina Rish, Saharon Rosset, Martin Slawski, Stephen C. Strother, Jagannadan Varadarajan, Eric P. Xing

Spectrum Sharing

Author : Constantinos B. Papadias
Publisher : John Wiley & Sons
ISBN 13 : 111955151X
Total Pages : 496 pages
Book Rating : 4.1/5 (195 download)

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Book Synopsis Spectrum Sharing by : Constantinos B. Papadias

Download or read book Spectrum Sharing written by Constantinos B. Papadias and published by John Wiley & Sons. This book was released on 2020-04-06 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: Combines the latest trends in spectrum sharing, both from a research and a standards/regulation/experimental standpoint Written by noted professionals from academia, industry, and research labs, this unique book provides a comprehensive treatment of the principles and architectures for spectrum sharing in order to help with the existing and future spectrum crunch issues. It presents readers with the most current standardization trends, including CEPT / CEE, eLSA, CBRS, MulteFire, LTE-Unlicensed (LTE-U), LTE WLAN integration with Internet Protocol security tunnel (LWIP), and LTE/Wi-Fi aggregation (LWA), and offers substantial trials and experimental results, as well as system-level performance evaluation results. The book also includes a chapter focusing on spectrum policy reinforcement and another on the economics of spectrum sharing. Beginning with the historic form of cognitive radio, Spectrum Sharing: The Next Frontier in Wireless Networks continues with current standardized forms of spectrum sharing, and reviews all of the technical ingredients that may arise in spectrum sharing approaches. It also looks at policy and implementation aspects and ponders the future of the field. White spaces and data base-assisted spectrum sharing are discussed, as well as the licensed shared access approach and cooperative communication techniques. The book also covers reciprocity-based beam forming techniques for spectrum sharing in MIMO networks; resource allocation for shared spectrum networks; large scale wireless spectrum monitoring; and much more. Contains all the latest standardization trends, such as CEPT / ECC, eLSA, CBRS, MulteFire, LTE-Unlicensed (LTE-U), LTE WLAN integration with Internet Protocol security tunnel (LWIP) and LTE/Wi-Fi aggregation (LWA) Presents a number of emerging technologies for future spectrum sharing (collaborative sensing, cooperative communication, reciprocity-based beamforming, etc.), as well as novel spectrum sharing paradigms (e.g. in full duplex and radar systems) Includes substantial trials and experimental results, as well as system-level performance evaluation results Contains a dedicated chapter on spectrum policy reinforcement and one on the economics of spectrum sharing Edited by experts in the field, and featuring contributions by respected professionals in the field world wide Spectrum Sharing: The Next Frontier in Wireless Networks is highly recommended for graduate students and researchers working in the areas of wireless communications and signal processing engineering. It would also benefit radio communications engineers and practitioners.

Robust Recognition via Information Theoretic Learning

Author : Ran He
Publisher : Springer
ISBN 13 : 3319074164
Total Pages : 120 pages
Book Rating : 4.3/5 (19 download)

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Book Synopsis Robust Recognition via Information Theoretic Learning by : Ran He

Download or read book Robust Recognition via Information Theoretic Learning written by Ran He and published by Springer. This book was released on 2014-08-28 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Springer Brief represents a comprehensive review of information theoretic methods for robust recognition. A variety of information theoretic methods have been proffered in the past decade, in a large variety of computer vision applications; this work brings them together, attempts to impart the theory, optimization and usage of information entropy. The authors resort to a new information theoretic concept, correntropy, as a robust measure and apply it to solve robust face recognition and object recognition problems. For computational efficiency, the brief introduces the additive and multiplicative forms of half-quadratic optimization to efficiently minimize entropy problems and a two-stage sparse presentation framework for large scale recognition problems. It also describes the strengths and deficiencies of different robust measures in solving robust recognition problems.

Research on the Key Technologies in Narrowband Interference and Impulsive Noise Mitigation and Cancellation

Author : Sicong Liu
Publisher : Springer Nature
ISBN 13 : 9811547246
Total Pages : 218 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Research on the Key Technologies in Narrowband Interference and Impulsive Noise Mitigation and Cancellation by : Sicong Liu

Download or read book Research on the Key Technologies in Narrowband Interference and Impulsive Noise Mitigation and Cancellation written by Sicong Liu and published by Springer Nature. This book was released on 2020-09-10 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book summarizes the authors’ latest research on narrowband interference and impulsive noise mitigation and cancelation, including (i) mitigating the impacts of NBI on synchronization; (ii) improving time-frequency interleaving performance under NBI and IN; (iii) accurately recovering and eliminating NBI and IN. The complicated, random and intensive narrowband interference and impulsive noise are a serious bottleneck of the next-generation wireless communications and Internet of things. This book also proposes effective and novel frameworks and algorithms, which will significantly improve the capability of mitigating and eliminating NBI and IN in the next-generation broadband communications systems. This book not only presents thorough theoretical models and algorithm design guidelines, but also provides adequate simulation and experimental engineering methods and results. The book is a valuable reference for those engaged in theoretical study, algorithm design and engineering practice in related fields, such as wireless communications, smart lighting, IoT and smart grid communications.

Statistical Learning with Sparsity

Author : Trevor Hastie
Publisher : CRC Press
ISBN 13 : 1498712177
Total Pages : 354 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Statistical Learning with Sparsity by : Trevor Hastie

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

Sparse Polynomial Approximation of High-Dimensional Functions

Author : Ben Adcock
Publisher : SIAM
ISBN 13 : 161197688X
Total Pages : 310 pages
Book Rating : 4.6/5 (119 download)

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Book Synopsis Sparse Polynomial Approximation of High-Dimensional Functions by : Ben Adcock

Download or read book Sparse Polynomial Approximation of High-Dimensional Functions written by Ben Adcock and published by SIAM. This book was released on 2022-02-16 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over seventy years ago, Richard Bellman coined the term “the curse of dimensionality” to describe phenomena and computational challenges that arise in high dimensions. These challenges, in tandem with the ubiquity of high-dimensional functions in real-world applications, have led to a lengthy, focused research effort on high-dimensional approximation—that is, the development of methods for approximating functions of many variables accurately and efficiently from data. This book provides an in-depth treatment of one of the latest installments in this long and ongoing story: sparse polynomial approximation methods. These methods have emerged as useful tools for various high-dimensional approximation tasks arising in a range of applications in computational science and engineering. It begins with a comprehensive overview of best s-term polynomial approximation theory for holomorphic, high-dimensional functions, as well as a detailed survey of applications to parametric differential equations. It then describes methods for computing sparse polynomial approximations, focusing on least squares and compressed sensing techniques. Sparse Polynomial Approximation of High-Dimensional Functions presents the first comprehensive and unified treatment of polynomial approximation techniques that can mitigate the curse of dimensionality in high-dimensional approximation, including least squares and compressed sensing. It develops main concepts in a mathematically rigorous manner, with full proofs given wherever possible, and it contains many numerical examples, each accompanied by downloadable code. The authors provide an extensive bibliography of over 350 relevant references, with an additional annotated bibliography available on the book’s companion website (www.sparse-hd-book.com). This text is aimed at graduate students, postdoctoral fellows, and researchers in mathematics, computer science, and engineering who are interested in high-dimensional polynomial approximation techniques.

Statistical Analysis for High-Dimensional Data

Author : Arnoldo Frigessi
Publisher : Springer
ISBN 13 : 3319270990
Total Pages : 313 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis Statistical Analysis for High-Dimensional Data by : Arnoldo Frigessi

Download or read book Statistical Analysis for High-Dimensional Data written by Arnoldo Frigessi and published by Springer. This book was released on 2016-02-16 with total page 313 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book features research contributions from The Abel Symposium on Statistical Analysis for High Dimensional Data, held in Nyvågar, Lofoten, Norway, in May 2014. The focus of the symposium was on statistical and machine learning methodologies specifically developed for inference in “big data” situations, with particular reference to genomic applications. The contributors, who are among the most prominent researchers on the theory of statistics for high dimensional inference, present new theories and methods, as well as challenging applications and computational solutions. Specific themes include, among others, variable selection and screening, penalised regression, sparsity, thresholding, low dimensional structures, computational challenges, non-convex situations, learning graphical models, sparse covariance and precision matrices, semi- and non-parametric formulations, multiple testing, classification, factor models, clustering, and preselection. Highlighting cutting-edge research and casting light on future research directions, the contributions will benefit graduate students and researchers in computational biology, statistics and the machine learning community.