Name
Title | ||
|---|---|---|
Manifold Proximal Point Algorithms for Dual Principal Component Pursuit and Orthogonal Dictionary Learning |
Abstract | ||
|---|---|---|
Dual principal component pursuit and orthogonal dictionary learning are two fundamental tools in data analysis, and both of them can be formulated as a manifold optimization problem with nonsmooth objective. Algorithms with convergence guarantees for solving this kind of problems have been very limited in the literature. In this paper, we propose a novel manifold proximal point algorithm for solving this nonsmooth manifold optimization problem. Numerical results are reported to demonstrate the effectiveness of the proposed algorithm. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/IEEECONF44664.2019.9048840 | 2019 53rd Asilomar Conference on Signals, Systems, and Computers |
Keywords | DocType | ISSN |
Manifold Optimization,Proximal Point Algorithm,Subspace Clustering,Dictionary Learning | Conference | 1058-6393 |
ISBN | Citations | PageRank |
978-1-7281-4301-9 | 0 | 0.34 |
References | Authors | |
12 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chen Shixiang | 1 | 0 | 0.34 |
| Zengde Deng | 2 | 2 | 1.72 |
| Shiqian Ma | 3 | 1068 | 63.48 |
| Anthony Man-cho So | 4 | 1821 | 99.32 |