Adaptive L1 Regularized Second-order Least Squares Method for Model Selection

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Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (135 download)

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Book Synopsis Adaptive L1 Regularized Second-order Least Squares Method for Model Selection by : Lin Xue

Download or read book Adaptive L1 Regularized Second-order Least Squares Method for Model Selection written by Lin Xue and published by . This book was released on 2015 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second-order least squares (SLS) method in regression model proposed by Wang (2003, 2004) is based on the first two conditional moments of the response variable given the observed predictor variables. Wang and Leblanc (2008) show that the SLS estimator (SLSE) is asymptotically more efficient than the ordinary least squares estimator (OLSE) if the third moment of the random error is nonzero. We apply the SLS method to variable selection problems and propose the adaptively weighted L1 regularized SLSE (L1-SLSE). The L1-SLSE is robust against the shape of error distributions in variable selection problems. Finite sample simulation studies show that the L1-SLSE is more efficient than L1-OLSE in the case of asymmetric error distributions. A real data application with L1-SLSE is presented to demonstrate the usage of this method.

Digital Signal Processing Handbook on CD-ROM

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Publisher : CRC Press
ISBN 13 : 0849321352
Total Pages : 1725 pages
Book Rating : 4.8/5 (493 download)

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Book Synopsis Digital Signal Processing Handbook on CD-ROM by : VIJAY MADISETTI

Download or read book Digital Signal Processing Handbook on CD-ROM written by VIJAY MADISETTI and published by CRC Press. This book was released on 1999-02-26 with total page 1725 pages. Available in PDF, EPUB and Kindle. Book excerpt: A best-seller in its print version, this comprehensive CD-ROM reference contains unique, fully searchable coverage of all major topics in digital signal processing (DSP), establishing an invaluable, time-saving resource for the engineering community. Its unique and broad scope includes contributions from all DSP specialties, including: telecommunications, computer engineering, acoustics, seismic data analysis, DSP software and hardware, image and video processing, remote sensing, multimedia applications, medical technology, radar and sonar applications

Adaptive Blind Signal and Image Processing

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Publisher : John Wiley & Sons
ISBN 13 : 9780471607915
Total Pages : 596 pages
Book Rating : 4.6/5 (79 download)

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Book Synopsis Adaptive Blind Signal and Image Processing by : Andrzej Cichocki

Download or read book Adaptive Blind Signal and Image Processing written by Andrzej Cichocki and published by John Wiley & Sons. This book was released on 2002-06-14 with total page 596 pages. Available in PDF, EPUB and Kindle. Book excerpt: Im Mittelpunkt dieses modernen und spezialisierten Bandes stehen adaptive Strukturen und unüberwachte Lernalgorithmen, besonders im Hinblick auf effektive Computersimulationsprogramme. Anschauliche Illustrationen und viele Beispiele sowie eine interaktive CD-ROM ergänzen den Text.

Fundamentals of Adaptive Signal Processing

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Publisher : Springer
ISBN 13 : 3319028073
Total Pages : 725 pages
Book Rating : 4.3/5 (19 download)

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Book Synopsis Fundamentals of Adaptive Signal Processing by : Aurelio Uncini

Download or read book Fundamentals of Adaptive Signal Processing written by Aurelio Uncini and published by Springer. This book was released on 2014-12-30 with total page 725 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an accessible guide to adaptive signal processing methods that equips the reader with advanced theoretical and practical tools for the study and development of circuit structures and provides robust algorithms relevant to a wide variety of application scenarios. Examples include multimodal and multimedia communications, the biological and biomedical fields, economic models, environmental sciences, acoustics, telecommunications, remote sensing, monitoring and in general, the modeling and prediction of complex physical phenomena. The reader will learn not only how to design and implement the algorithms but also how to evaluate their performance for specific applications utilizing the tools provided. While using a simple mathematical language, the employed approach is very rigorous. The text will be of value both for research purposes and for courses of study.

Adaptive Regression

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Publisher : Springer Science & Business Media
ISBN 13 : 1441987665
Total Pages : 188 pages
Book Rating : 4.4/5 (419 download)

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Book Synopsis Adaptive Regression by : Yadolah Dodge

Download or read book Adaptive Regression written by Yadolah Dodge and published by Springer Science & Business Media. This book was released on 2012-10-01 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: While there have been a large number of estimation methods proposed and developed for linear regression, none has proved good for all purposes. This text focuses on the construction of an adaptive combination of two estimation methods so as to help users make an objective choice and combine the desirable properties of two estimators.

Adaptive Learning Methods for Nonlinear System Modeling

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Publisher : Butterworth-Heinemann
ISBN 13 : 0128129778
Total Pages : 390 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Adaptive Learning Methods for Nonlinear System Modeling by : Danilo Comminiello

Download or read book Adaptive Learning Methods for Nonlinear System Modeling written by Danilo Comminiello and published by Butterworth-Heinemann. This book was released on 2018-06-11 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive Learning Methods for Nonlinear System Modeling presents some of the recent advances on adaptive algorithms and machine learning methods designed for nonlinear system modeling and identification. Real-life problems always entail a certain degree of nonlinearity, which makes linear models a non-optimal choice. This book mainly focuses on those methodologies for nonlinear modeling that involve any adaptive learning approaches to process data coming from an unknown nonlinear system. By learning from available data, such methods aim at estimating the nonlinearity introduced by the unknown system. In particular, the methods presented in this book are based on online learning approaches, which process the data example-by-example and allow to model even complex nonlinearities, e.g., showing time-varying and dynamic behaviors. Possible fields of applications of such algorithms includes distributed sensor networks, wireless communications, channel identification, predictive maintenance, wind prediction, network security, vehicular networks, active noise control, information forensics and security, tracking control in mobile robots, power systems, and nonlinear modeling in big data, among many others. This book serves as a crucial resource for researchers, PhD and post-graduate students working in the areas of machine learning, signal processing, adaptive filtering, nonlinear control, system identification, cooperative systems, computational intelligence. This book may be also of interest to the industry market and practitioners working with a wide variety of nonlinear systems. Presents the key trends and future perspectives in the field of nonlinear signal processing and adaptive learning. Introduces novel solutions and improvements over the state-of-the-art methods in the very exciting area of online and adaptive nonlinear identification. Helps readers understand important methods that are effective in nonlinear system modelling, suggesting the right methodology to address particular issues.

Hands-On Machine Learning with R

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Publisher : CRC Press
ISBN 13 : 1000730433
Total Pages : 374 pages
Book Rating : 4.0/5 (7 download)

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Book Synopsis Hands-On Machine Learning with R by : Brad Boehmke

Download or read book Hands-On Machine Learning with R written by Brad Boehmke and published by CRC Press. This book was released on 2019-11-07 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hands-on Machine Learning with R provides a practical and applied approach to learning and developing intuition into today’s most popular machine learning methods. This book serves as a practitioner’s guide to the machine learning process and is meant to help the reader learn to apply the machine learning stack within R, which includes using various R packages such as glmnet, h2o, ranger, xgboost, keras, and others to effectively model and gain insight from their data. The book favors a hands-on approach, providing an intuitive understanding of machine learning concepts through concrete examples and just a little bit of theory. Throughout this book, the reader will be exposed to the entire machine learning process including feature engineering, resampling, hyperparameter tuning, model evaluation, and interpretation. The reader will be exposed to powerful algorithms such as regularized regression, random forests, gradient boosting machines, deep learning, generalized low rank models, and more! By favoring a hands-on approach and using real word data, the reader will gain an intuitive understanding of the architectures and engines that drive these algorithms and packages, understand when and how to tune the various hyperparameters, and be able to interpret model results. By the end of this book, the reader should have a firm grasp of R’s machine learning stack and be able to implement a systematic approach for producing high quality modeling results. Features: · Offers a practical and applied introduction to the most popular machine learning methods. · Topics covered include feature engineering, resampling, deep learning and more. · Uses a hands-on approach and real world data.

Mathematical Methods in Engineering

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Publisher : Springer
ISBN 13 : 331990972X
Total Pages : 266 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Mathematical Methods in Engineering by : Kenan Taş

Download or read book Mathematical Methods in Engineering written by Kenan Taş and published by Springer. This book was released on 2018-08-02 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent developments in nonlinear dynamics with an emphasis on complex systems. The volume illustrates new methods to characterize the solutions of nonlinear dynamics associated with complex systems. This book contains the following topics: new solutions of the functional equations, optimization algorithm for traveling salesman problem, fractals, control, fractional calculus models, fractional discretization, local fractional partial differential equations and their applications, and solutions of fractional kinetic equations.

Sparse Linear Models and L1-Regularized 2SLS with High-Dimensional Endogenous Regressors and Instruments

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Publisher :
ISBN 13 :
Total Pages : 37 pages
Book Rating : 4.:/5 (13 download)

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Book Synopsis Sparse Linear Models and L1-Regularized 2SLS with High-Dimensional Endogenous Regressors and Instruments by : Ying Zhu

Download or read book Sparse Linear Models and L1-Regularized 2SLS with High-Dimensional Endogenous Regressors and Instruments written by Ying Zhu and published by . This book was released on 2018 with total page 37 pages. Available in PDF, EPUB and Kindle. Book excerpt: We explore the validity of the 2-stage least squares estimator with l_{1}-regularization in both stages, for linear triangular models where the numbers of endogenous regressors in the main equation and instruments in the first-stage equations can exceed the sample size, and the regression coefficients are sufficiently sparse. For this l_{1}-regularized 2-stage least squares estimator, we first establish finite-sample performance bounds and then provide a simple practical method (with asymptotic guarantees) for choosing the regularization parameter. We also sketch an inference strategy built upon this practical method.

Machine Learning

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Publisher : MIT Press
ISBN 13 : 0262304325
Total Pages : 1102 pages
Book Rating : 4.2/5 (623 download)

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Book Synopsis Machine Learning by : Kevin P. Murphy

Download or read book Machine Learning written by Kevin P. Murphy and published by MIT Press. This book was released on 2012-09-07 with total page 1102 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive introduction to machine learning that uses probabilistic models and inference as a unifying approach. Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach. The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package—PMTK (probabilistic modeling toolkit)—that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.

Comprehensive Chemometrics

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Publisher : Elsevier
ISBN 13 : 044452701X
Total Pages : 2880 pages
Book Rating : 4.4/5 (445 download)

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Book Synopsis Comprehensive Chemometrics by :

Download or read book Comprehensive Chemometrics written by and published by Elsevier. This book was released on 2009-03-09 with total page 2880 pages. Available in PDF, EPUB and Kindle. Book excerpt: Designed to serve as the first point of reference on the subject, Comprehensive Chemometrics presents an integrated summary of the present state of chemical and biochemical data analysis and manipulation. The work covers all major areas ranging from statistics to data acquisition, analysis, and applications. This major reference work provides broad-ranging, validated summaries of the major topics in chemometrics—with chapter introductions and advanced reviews for each area. The level of material is appropriate for graduate students as well as active researchers seeking a ready reference on obtaining and analyzing scientific data. Features the contributions of leading experts from 21 countries, under the guidance of the Editors-in-Chief and a team of specialist Section Editors: L. Buydens; D. Coomans; P. Van Espen; A. De Juan; J.H. Kalivas; B.K. Lavine; R. Leardi; R. Phan-Tan-Luu; L.A. Sarabia; and J. Trygg Examines the merits and limitations of each technique through practical examples and extensive visuals: 368 tables and more than 1,300 illustrations (750 in full color) Integrates coverage of chemical and biological methods, allowing readers to consider and test a range of techniques Consists of 2,200 pages and more than 90 review articles, making it the most comprehensive work of its kind Offers print and online purchase options, the latter of which delivers flexibility, accessibility, and usability through the search tools and other productivity-enhancing features of ScienceDirect

Evaluation Complexity of Algorithms for Nonconvex Optimization

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Publisher : SIAM
ISBN 13 : 1611976995
Total Pages : 549 pages
Book Rating : 4.6/5 (119 download)

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Book Synopsis Evaluation Complexity of Algorithms for Nonconvex Optimization by : Coralia Cartis

Download or read book Evaluation Complexity of Algorithms for Nonconvex Optimization written by Coralia Cartis and published by SIAM. This book was released on 2022-07-06 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: A popular way to assess the “effort” needed to solve a problem is to count how many evaluations of the problem functions (and their derivatives) are required. In many cases, this is often the dominating computational cost. Given an optimization problem satisfying reasonable assumptions—and given access to problem-function values and derivatives of various degrees—how many evaluations might be required to approximately solve the problem? Evaluation Complexity of Algorithms for Nonconvex Optimization: Theory, Computation, and Perspectives addresses this question for nonconvex optimization problems, those that may have local minimizers and appear most often in practice. This is the first book on complexity to cover topics such as composite and constrained optimization, derivative-free optimization, subproblem solution, and optimal (lower and sharpness) bounds for nonconvex problems. It is also the first to address the disadvantages of traditional optimality measures and propose useful surrogates leading to algorithms that compute approximate high-order critical points, and to compare traditional and new methods, highlighting the advantages of the latter from a complexity point of view. This is the go-to book for those interested in solving nonconvex optimization problems. It is suitable for advanced undergraduate and graduate students in courses on advanced numerical analysis, data science, numerical optimization, and approximation theory.

Adaptive Systems in Control and Signal Processing 1992

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Publisher : Elsevier
ISBN 13 : 1483298809
Total Pages : 557 pages
Book Rating : 4.4/5 (832 download)

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Book Synopsis Adaptive Systems in Control and Signal Processing 1992 by : L. Dugard

Download or read book Adaptive Systems in Control and Signal Processing 1992 written by L. Dugard and published by Elsevier. This book was released on 2014-06-28 with total page 557 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive Systems remain a very interesting field of theoretical research, extended by methodological studies and an increasing number of applications. The plenary papers, invited sessions and contributed sessions focused on many aspects of adaptive systems, such as systems identification and modelling, adaptive control of nonlinear systems and theoretical issues in adaptive control. Also covered were methodological aspects and applications of adaptive control, intelligent tuning and adaptive signal processing.

Statistical Learning with Sparsity

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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

Modeling and Analysis of Longitudinal Data

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Publisher : Elsevier
ISBN 13 : 0443136521
Total Pages : 362 pages
Book Rating : 4.4/5 (431 download)

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Book Synopsis Modeling and Analysis of Longitudinal Data by :

Download or read book Modeling and Analysis of Longitudinal Data written by and published by Elsevier. This book was released on 2024-02-20 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: Longitudinal Data Analysis, Volume 50 in the Handbook of Statistics series covers how data consists of a series of repeated observations of the same subjects over an extended time frame and is thus useful for measuring change. Such studies and the data arise in a variety of fields, such as health sciences, genomic studies, experimental physics, sociology, sports and student enrollment in universities. For example, in health studies, intra-subject correlation of responses must be accounted for, covariates vary with time, and bias can arise if patients drop out of the study. Provides the authority and expertise of leading contributors from an international board of authors Presents the latest release in the Handbook of Statistics series Updated release includes the latest information on Modeling and Analysis of Longitudinal Data

Translational Multimodality Optical Imaging

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Publisher : Artech House
ISBN 13 : 1596933089
Total Pages : 431 pages
Book Rating : 4.5/5 (969 download)

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Book Synopsis Translational Multimodality Optical Imaging by : Fred S. Azar

Download or read book Translational Multimodality Optical Imaging written by Fred S. Azar and published by Artech House. This book was released on 2008 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: Supported with 119 illustrations, this milestone work discusses key optical imaging techniques in self-contained chapters; describes the integration of optical imaging techniques with other modalities like MRI, X-ray imaging, and PET imaging; provides a software platform for multimodal integration; presents cutting-edge computational and data processing techniques that ensure rapid, cost-effective, and precise quantification and characterization of the clinical data; covers advances in photodynamic therapy and molecular imaging, and reviews key clinical studies in optical imaging along with regulatory and business issues.

Winter Annual Meeting

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Publisher :
ISBN 13 :
Total Pages : 776 pages
Book Rating : 4.0/5 ( download)

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Book Synopsis Winter Annual Meeting by : American Society of Mechanical Engineers

Download or read book Winter Annual Meeting written by American Society of Mechanical Engineers and published by . This book was released on with total page 776 pages. Available in PDF, EPUB and Kindle. Book excerpt: