Limit search to available items
Book Cover
E-book
Author Bahmani, Sohail, author

Title Algorithms for sparsity-constrained optimization / Sohail Bahmani
Published Cham : Springer, 2014

Copies

Description 1 online resource (xxi, 107 pages) : illustrations (some color)
Series Springer Theses, 2190-5053
Springer theses.
Contents Introduction -- Preliminaries -- Sparsity-Constrained Optimization -- Background -- 1-bit Compressed Sensing -- Estimation Under Model-Based Sparsity -- Projected Gradient Descent for lp-constrained Least Squares -- Conclusion and Future Work
Summary This thesis demonstrates techniques that provide faster and more accurate solutions to a variety of problems in machine learning and signal processing. The author proposes a"greedy" algorithm, deriving sparse solutions with guarantees of optimality. The use of this algorithm removes many of the inaccuracies that occurred with the use of previous models
Notes Ph. D. Carnegie Mellon University (2013?)
Bibliography Includes bibliographical references
Notes Online resource; title from PDF title page (SpringerLink, viewed October 14, 2013)
Subject Mathematical optimization.
MATHEMATICS -- Applied.
MATHEMATICS -- Probability & Statistics -- General.
Mathematical optimization
Genre/Form doctoral dissertations.
masters theses.
dissertations.
theses.
Academic theses
Academic theses.
Thèses et écrits académiques.
Form Electronic book
ISBN 9783319018812
3319018817
3319018809
9783319018805