Algorithms for sparsity-constrained optimization
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 o...
| Main Author: | Bahmani, Sohail, |
|---|---|
| Other Authors: | SpringerLink (Online service) |
| Format: | eBook |
| Language: | English |
| Published: |
Cham :
Springer,
2014.
|
| Physical Description: |
1 online resource (xxi, 107 pages) : illustrations (some color). |
| Series: |
Springer theses.
|
| Subjects: |
CMU Electronic Access
Electronic Resource Click Here| Location | Call Number: | Status |
|---|---|---|
| CMU Electronic Access | Available |