Abstract
A greedy algorithm for a class of convex optimization problems is presented in this paper. The algorithm is motivated from function approximation using sparse combination of basis functions as well as some of its variants. We derive a bound on the rate of approximate minimization for this algorithm, and present examples of its application. Our analysis generalizes a number of earlier studies.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 682-691 |
| Number of pages | 10 |
| Journal | IEEE Transactions on Information Theory |
| Volume | 49 |
| Issue number | 3 |
| DOIs | |
| State | Published - Mar 2003 |
| Externally published | Yes |
Keywords
- Boosting
- Greedy approximation
- Incremental algorithms
- Rate of approximate optimization
- Sparse approximation
ASJC Scopus subject areas
- Information Systems
- Computer Science Applications
- Library and Information Sciences
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