Algorithms for Sparsity-Constrained Optimization
tarafından
Bahmani, Sohail. author.
Başlık
:
Algorithms for Sparsity-Constrained Optimization
Yazar
:
Bahmani, Sohail. author.
ISBN
:
9783319018812
Yazar
:
Bahmani, Sohail. author.
Fiziksel Niteleme
:
XXI, 107 p. 13 illus., 12 illus. in color. online resource.
Seri
:
Springer Theses, Recognizing Outstanding Ph.D. Research, 261
İçindekiler
:
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.
Özet
:
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.
Konu Başlığı
:
Engineering.
Image processing.
Computer science -- Mathematics.
Computer mathematics.
Signal, Image and Speech Processing.
Mathematical Applications in Computer Science.
Image Processing and Computer Vision.
Ek Kurum Yazar
:
SpringerLink (Online service)
Elektronik Erişim
:
| Materyal Türü | Barkod | Yer Numarası | Durumu/İade Tarihi |
|---|
| Electronic Book | 20141-1001 | TK5102.9 | Springer E-Book Collection |