A Regularized Active-Set method For Sparse Convex Quadratic Programming

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Publisher : Stanford University
ISBN 13 :
Total Pages : 128 pages
Book Rating : 4./5 ( download)

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Book Synopsis A Regularized Active-Set method For Sparse Convex Quadratic Programming by :

Download or read book A Regularized Active-Set method For Sparse Convex Quadratic Programming written by and published by Stanford University. This book was released on with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt:

A Regularized Active-set Method for Sparse Convex Quadratic Programming

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Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (688 download)

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Book Synopsis A Regularized Active-set Method for Sparse Convex Quadratic Programming by : Christopher Mario Maes

Download or read book A Regularized Active-set Method for Sparse Convex Quadratic Programming written by Christopher Mario Maes and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: An active-set algorithm is developed for solving convex quadratic programs (QPs). The algorithm employs primal regularization within a bound-constrained augmented Lagrangian method. This leads to a sequence of QP subproblems that are feasible and strictly convex, and whose KKT systems are guaranteed to be nonsingular for any active set. A simplified, single-phase algorithm becomes possible for each QP subproblem. There is no need to control the inertia of the KKT system defining each search direction, and a simple step-length procedure may be used without risk of cycling in the presence of degeneracy. Since all KKT systems are nonsingular, they can be factored with a variety of sparse direct linear solvers. Block-LU updates of the KKT factors allow for active-set changes. The principal benefit of primal and dual regularization is that warm starts are possible from any given active set. This is vital inside sequential quadratic programming (SQP) methods for nonlinear optimization, such as the SNOPT solver. The method provides a reliable approach to solving sparse generalized least-squares problems. Ordinary least-squares problems with Tikhonov regularization and bounds can be solved as a single QP subproblem. The algorithm is implemented as the QPBLUR solver (Matlab and Fortran 95 versions) and the Fortran version has been integrated into SNOPT. The performance of QPBLUR is evaluated on a test set of large convex QPs, and on the sequences of QPs arising from SNOPT's SQP method.

Multiphysics Phase-Field Fracture

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Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3110497395
Total Pages : 358 pages
Book Rating : 4.1/5 (14 download)

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Book Synopsis Multiphysics Phase-Field Fracture by : Thomas Wick

Download or read book Multiphysics Phase-Field Fracture written by Thomas Wick and published by Walter de Gruyter GmbH & Co KG. This book was released on 2020-10-12 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph is centered on mathematical modeling, innovative numerical algorithms and adaptive concepts to deal with fracture phenomena in multiphysics. State-of-the-art phase-field fracture models are complemented with prototype explanations and rigorous numerical analysis. These developments are embedded into a carefully designed balance between scientific computing aspects and numerical modeling of nonstationary coupled variational inequality systems. Therein, a focus is on nonlinear solvers, goal-oriented error estimation, predictor-corrector adaptivity, and interface conditions. Engineering applications show the potential for tackling practical problems within the fields of solid mechanics, porous media, and fluidstructure interaction.

Mixed Integer Nonlinear Programming

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Publisher : Springer Science & Business Media
ISBN 13 : 1461419271
Total Pages : 687 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Mixed Integer Nonlinear Programming by : Jon Lee

Download or read book Mixed Integer Nonlinear Programming written by Jon Lee and published by Springer Science & Business Media. This book was released on 2011-12-02 with total page 687 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many engineering, operations, and scientific applications include a mixture of discrete and continuous decision variables and nonlinear relationships involving the decision variables that have a pronounced effect on the set of feasible and optimal solutions. Mixed-integer nonlinear programming (MINLP) problems combine the numerical difficulties of handling nonlinear functions with the challenge of optimizing in the context of nonconvex functions and discrete variables. MINLP is one of the most flexible modeling paradigms available for optimization; but because its scope is so broad, in the most general cases it is hopelessly intractable. Nonetheless, an expanding body of researchers and practitioners — including chemical engineers, operations researchers, industrial engineers, mechanical engineers, economists, statisticians, computer scientists, operations managers, and mathematical programmers — are interested in solving large-scale MINLP instances.

A Single-phase Method for Quadratic Programming

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Publisher :
ISBN 13 :
Total Pages : 80 pages
Book Rating : 4.F/5 ( download)

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Book Synopsis A Single-phase Method for Quadratic Programming by : Stanford University. Systems Optimization Laboratory

Download or read book A Single-phase Method for Quadratic Programming written by Stanford University. Systems Optimization Laboratory and published by . This book was released on 1986 with total page 80 pages. Available in PDF, EPUB and Kindle. Book excerpt: This report describes a single-phase quadratic programming method, an active-set method which solves a sequence of equality-constraint quadratic programs.

Schur-complement Method for Sparse Quadratic Programming

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Publisher :
ISBN 13 :
Total Pages : 34 pages
Book Rating : 4.F/5 ( download)

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Book Synopsis Schur-complement Method for Sparse Quadratic Programming by : Stanford University. Systems Optimization Laboratory

Download or read book Schur-complement Method for Sparse Quadratic Programming written by Stanford University. Systems Optimization Laboratory and published by . This book was released on 1987 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt: Moreover, improvements in efficiency derived from exploiting new parallel and vector computer architectures are immediately applicable. An obvious application of the method is in sequential quadratic programming methods for nonlinearly constrained optimization, which require solution of a sequence of closely related quadratic programming subproblems. We discuss some ways in which the known relationship between successive problems can be exploited."

A Primal-dual Active-set Method for Convex Quadratic Programming

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Publisher :
ISBN 13 :
Total Pages : 20 pages
Book Rating : 4.:/5 (767 download)

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Book Synopsis A Primal-dual Active-set Method for Convex Quadratic Programming by : Ekaterina A. Kostina

Download or read book A Primal-dual Active-set Method for Convex Quadratic Programming written by Ekaterina A. Kostina and published by . This book was released on 2003 with total page 20 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Solving Large Sparse Quadratic Programs with Simple Bounds

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Publisher :
ISBN 13 :
Total Pages : 288 pages
Book Rating : 4.E/5 ( download)

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Book Synopsis Solving Large Sparse Quadratic Programs with Simple Bounds by : Laurie Ann Hulbert

Download or read book Solving Large Sparse Quadratic Programs with Simple Bounds written by Laurie Ann Hulbert and published by . This book was released on 1990 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt:

A Direct Active Set Algorithm for Large Sparse Quadratic Programs with Simple Bounds

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Publisher :
ISBN 13 :
Total Pages : 36 pages
Book Rating : 4.:/5 (25 download)

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Book Synopsis A Direct Active Set Algorithm for Large Sparse Quadratic Programs with Simple Bounds by : Cornell University. Dept. of Computer Science

Download or read book A Direct Active Set Algorithm for Large Sparse Quadratic Programs with Simple Bounds written by Cornell University. Dept. of Computer Science and published by . This book was released on 1988 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt: We show how a direct active set method for solving definite and indefinite quadratic programs with simple bounds can be efficiently implemented for large sparse problems. All of the necessary factorizations can be carried out in a static data structure that is set up before the numeric computation begins. The space required for these factorizations is no larger than that required for a single sparse Cholesky factorization of a matrix with the same sparsity structure as the Hessian of the quadratic. We propose several improvements to this basic algorithm: a new way to find a search direction in the indefinite case that allows us to free more than one variable at a time and a new heuristic method for finding a starting point. These ideas are motivated by the two-norm trust region problem. Additionally, we also show how projection techniques can be used to add several constraints to the active set at each iteration. Our experimental results show that an algorithm with these improvements runs much faster than the basic algorithm for positive definite problems and finds local minima with lower function values for indefinite problems.

Neural Networks and Statistical Learning

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Publisher : Springer Nature
ISBN 13 : 1447174526
Total Pages : 988 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Neural Networks and Statistical Learning by : Ke-Lin Du

Download or read book Neural Networks and Statistical Learning written by Ke-Lin Du and published by Springer Nature. This book was released on 2019-09-12 with total page 988 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a broad yet detailed introduction to neural networks and machine learning in a statistical framework. A single, comprehensive resource for study and further research, it explores the major popular neural network models and statistical learning approaches with examples and exercises and allows readers to gain a practical working understanding of the content. This updated new edition presents recently published results and includes six new chapters that correspond to the recent advances in computational learning theory, sparse coding, deep learning, big data and cloud computing. Each chapter features state-of-the-art descriptions and significant research findings. The topics covered include: • multilayer perceptron; • the Hopfield network; • associative memory models;• clustering models and algorithms; • t he radial basis function network; • recurrent neural networks; • nonnegative matrix factorization; • independent component analysis; •probabilistic and Bayesian networks; and • fuzzy sets and logic. Focusing on the prominent accomplishments and their practical aspects, this book provides academic and technical staff, as well as graduate students and researchers with a solid foundation and comprehensive reference on the fields of neural networks, pattern recognition, signal processing, and machine learning.

Signal Processing and Networking for Big Data Applications

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Publisher : Cambridge University Press
ISBN 13 : 1108155944
Total Pages : 375 pages
Book Rating : 4.1/5 (81 download)

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Book Synopsis Signal Processing and Networking for Big Data Applications by : Zhu Han

Download or read book Signal Processing and Networking for Big Data Applications written by Zhu Han and published by Cambridge University Press. This book was released on 2017-04-27 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique text helps make sense of big data in engineering applications using tools and techniques from signal processing. It presents fundamental signal processing theories and software implementations, reviews current research trends and challenges, and describes the techniques used for analysis, design and optimization. Readers will learn about key theoretical issues such as data modelling and representation, scalable and low-complexity information processing and optimization, tensor and sublinear algorithms, and deep learning and software architecture, and their application to a wide range of engineering scenarios. Applications discussed in detail include wireless networking, smart grid systems, and sensor networks and cloud computing. This is the ideal text for researchers and practising engineers wanting to solve practical problems involving large amounts of data, and for students looking to grasp the fundamentals of big data analytics.

Active-set Methods for Quadratic Programming

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Publisher :
ISBN 13 : 9781124691152
Total Pages : 125 pages
Book Rating : 4.6/5 (911 download)

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Book Synopsis Active-set Methods for Quadratic Programming by : Elizabeth Lai Sum Wong

Download or read book Active-set Methods for Quadratic Programming written by Elizabeth Lai Sum Wong and published by . This book was released on 2011 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational methods are considered for finding a point satisfying the second-order necessary conditions for a general (possibly nonconvex) quadratic program (QP). A framework for the formulation and analysis of feasible-point active-set methods is proposed for a generic QP. This framework is defined by reformulating and extending an inertia-controlling method for general QP that was first proposed by Fletcher and subsequently modified by Gould. This reformulation defines a class of methods in which a primal-dual search pair is the solution of a "KKT system'' of equations associated with an equality-constrained QP subproblem defined in terms of a "working set'' of linearly independent constraints. It is shown that, under certain circumstances, the solution of this KKT system may be updated using a simple recurrence relation, thereby giving a significant reduction in the number of systems that need to be solved. The use of inertia control guarantees that the KKT systems remain nonsingular throughout, thereby allowing the utilization of third-party linear algebra software. The algorithm is suitable for indefinite problems, making it an ideal QP solver for stand-alone applications and for use within a sequential quadratic programming method using exact second derivatives. The proposed framework is applied to primal and dual quadratic problems, as well as to single-phase problems that combine the feasibility and optimality phases of the active-set method, producing a range of formats that are suitable for a variety of applications. The algorithm is implemented in the Fortran code icQP. Its performance is evaluated using different symmetric and unsymmetric linear solvers on a set of convex and nonconvex problems. Results are presented that compare the performance of icQP with the convex QP solver SQOPT on a large set of convex problems.

Barrier Methods for Large-scale Quadratic Programming

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Publisher :
ISBN 13 :
Total Pages : 142 pages
Book Rating : 4.F/5 ( download)

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Book Synopsis Barrier Methods for Large-scale Quadratic Programming by : Stanford University. Department of Operations Research. Systems Optimization Laboratory

Download or read book Barrier Methods for Large-scale Quadratic Programming written by Stanford University. Department of Operations Research. Systems Optimization Laboratory and published by . This book was released on 1991 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Sequential Quadratic Programming Algorithm Using an Incomplete Solution of the Subproblem

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Publisher :
ISBN 13 :
Total Pages : 48 pages
Book Rating : 4.F/5 ( download)

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Book Synopsis Sequential Quadratic Programming Algorithm Using an Incomplete Solution of the Subproblem by : Stanford University. Department of Operations Research. Systems Optimization Laboratory

Download or read book Sequential Quadratic Programming Algorithm Using an Incomplete Solution of the Subproblem written by Stanford University. Department of Operations Research. Systems Optimization Laboratory and published by . This book was released on 1990 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Predictive Control for Linear and Hybrid Systems

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Publisher : Cambridge University Press
ISBN 13 : 1107016886
Total Pages : 447 pages
Book Rating : 4.1/5 (7 download)

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Book Synopsis Predictive Control for Linear and Hybrid Systems by : Francesco Borrelli

Download or read book Predictive Control for Linear and Hybrid Systems written by Francesco Borrelli and published by Cambridge University Press. This book was released on 2017-06-22 with total page 447 pages. Available in PDF, EPUB and Kindle. Book excerpt: With a simple approach that includes real-time applications and algorithms, this book covers the theory of model predictive control (MPC).

Optimization with Sparsity-Inducing Penalties

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Publisher :
ISBN 13 : 9781601985101
Total Pages : 124 pages
Book Rating : 4.9/5 (851 download)

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Book Synopsis Optimization with Sparsity-Inducing Penalties by : Francis Bach

Download or read book Optimization with Sparsity-Inducing Penalties written by Francis Bach and published by . This book was released on 2011-12-23 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sparse estimation methods are aimed at using or obtaining parsimonious representations of data or models. They were first dedicated to linear variable selection but numerous extensions have now emerged such as structured sparsity or kernel selection. It turns out that many of the related estimation problems can be cast as convex optimization problems by regularizing the empirical risk with appropriate nonsmooth norms. Optimization with Sparsity-Inducing Penalties presents optimization tools and techniques dedicated to such sparsity-inducing penalties from a general perspective. It covers proximal methods, block-coordinate descent, reweighted ?2-penalized techniques, working-set and homotopy methods, as well as non-convex formulations and extensions, and provides an extensive set of experiments to compare various algorithms from a computational point of view. The presentation of Optimization with Sparsity-Inducing Penalties is essentially based on existing literature, but the process of constructing a general framework leads naturally to new results, connections and points of view. It is an ideal reference on the topic for anyone working in machine learning and related areas.

Electrical & Electronics Abstracts

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Publisher :
ISBN 13 :
Total Pages : 2240 pages
Book Rating : 4.3/5 (243 download)

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Book Synopsis Electrical & Electronics Abstracts by :

Download or read book Electrical & Electronics Abstracts written by and published by . This book was released on 1997 with total page 2240 pages. Available in PDF, EPUB and Kindle. Book excerpt: