| Github | Browse our lab repository here |
| NuMax | Learning near-isometric embeddings using semi-definite programming |
A linear dimensionality reduction technique that is near-isometric, i.e., preserves pairwise distances on a dataset. The codebase has an efficient implementation that uses a greedy procedure to obtain a superset of the active constraints. It is also possible to incorporate classification promoting objectives. | |
| (code) (paper) | |
| CS-MUVI | Video compressive sensing using motion-flow models |
| (code) (paper) | |
| SpaRCS | Compressive recovery of low rank + sparse matrices |
A greedy algorithm for compressive recovery of a matrix modeled as a sum of low-rank and sparse matrices. This approach uses a variant of CoSamp and Admira to achieve this. |
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| (code) (paper) | |
| CS-LDS | Linear dynamical system parameters from compressive measurements |
| (code) (paper) | |
