Algorithms for Sparsity-Constrained Optimization
Bahmani, Sohail.
Algorithms for Sparsity-Constrained Optimization [electronic resource] / by Sohail Bahmani. - XXI, 107 p. 13 illus., 12 illus. in color. online resource. - Springer Theses, Recognizing Outstanding Ph.D. Research, 261 2190-5053 ; . - Springer Theses, Recognizing Outstanding Ph.D. Research, 261 .
Introduction -- Preliminaries -- Sparsity-Constrained Optimization -- Background -- 1-bit Compressed Sensing -- Estimation Under Model-Based Sparsity -- Projected Gradient Descent for `p-constrained Least Squares -- Conclusion and Future Work.
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.
9783319018812
10.1007/978-3-319-01881-2 doi
Engineering.
Computer vision.
Engineering.
Signal, Image and Speech Processing.
Mathematical Applications in Computer Science.
Image Processing and Computer Vision.
TK5102.9 TA1637-1638 TK7882.S65
621.382
Algorithms for Sparsity-Constrained Optimization [electronic resource] / by Sohail Bahmani. - XXI, 107 p. 13 illus., 12 illus. in color. online resource. - Springer Theses, Recognizing Outstanding Ph.D. Research, 261 2190-5053 ; . - Springer Theses, Recognizing Outstanding Ph.D. Research, 261 .
Introduction -- Preliminaries -- Sparsity-Constrained Optimization -- Background -- 1-bit Compressed Sensing -- Estimation Under Model-Based Sparsity -- Projected Gradient Descent for `p-constrained Least Squares -- Conclusion and Future Work.
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.
9783319018812
10.1007/978-3-319-01881-2 doi
Engineering.
Computer vision.
Engineering.
Signal, Image and Speech Processing.
Mathematical Applications in Computer Science.
Image Processing and Computer Vision.
TK5102.9 TA1637-1638 TK7882.S65
621.382