See also textbooks.
Compressed sensing resources
These are well established internet sites on sparse approximation and compressed sensing
- Compressive sensing resources at Rice University. They maintain a nearly comprehensive list; you can email them and they will probably add your paper/solver to the list.
- Nuit Blanche is a blog by Igor Carron that is quite popular. He also maintains a more static webpage called The Big Picture in Compressive Sensing (which has a list of sparse recovery solvers). He also edits the Matrix Factorization Jungle page that features an up-to-date collection of matrix factorization implementations (low rank, NMF, randomized algorithms,....). Actual hardware implementation of compressive sensing can be found embedded in this list of compressive sensing sensors.
- An Introduction to Compressive Sensing online course at connexions. Written by Hedge, Laska, Duarte, Davenport, Sheikh, Baraniuk and Yin.
Lists of solvers
- Arvind Ganesh/Yi Ma's list on matrix completion
- list at OptSpace.
- Igor Carron has a comprehensive and up-to-date list of Sparse Recovery Solvers and a list of diverse Advanced Matrix Factorization implementations.
- There's a list at CS resources at Rice if you scroll to the very bottom of the page (and see the "Compressive Sensing Recovery Algorithms" section too).
- Allen Yang has a list and comparison of l1 solvers
- There's also a list of solvers developed at Rice University (e.g. FPC, YALL1).
Smaller and/or personal websites
please feel free to add your own website
Curated Technical Pages
- Curated Technical Pages
- Sparse Recovery
- Compressive Sensing Resources at Rice University
- The Big Picture in Compressive Sensing
- Phase Transitions of the Regular Polytopes and Cone at University of Edinburgh maintained by Jared Tanner.
- The Donoho-Tanner Phase transition for sparse recovery page by Igor Carron
- 1-bit compressive sensing at Rice University
- The LASSO page by Rob Tibshirani
- Count-Min Sketch and its application by Muthu Muthukrishnan and Andrew McGregor
- Low Rank
- Sparse Recovery
- RecSysWiki is about everything related to recommender systems (as in the Netflix prize).
- Nuit Blanche (Matrix Factorization , Compressive Sensing) by Igor Carron
- What's New by Terry Tao(Compressive Sensing)
- Rich Baraniuk
- Pursuit in the Null Space by Bob Sturm
- Zhilin Scientific Journey by Zhilin Zhang
- My Slice of Pizza by Muthu Muthukrishnan (Sketching, streaming)
- Polylog Blog by Andrew McGregor
- Tianyi Zhou Research Blog by Tianyi Zhou
- Regularize by Dirk Lorenz
- Large Scale Machine Learning and Other Animals by Danny Bickson
- La vertu d'un La by Laurent Duval
- Le Petit Chercheur Illustré by Laurent Jacques
- Espace Vide by Eric Tramel
- Discussion groups on LinkedIn (you need to join LinkedIn to be member of these groups]
Other Technical Pages
- NEOS wiki hosted at U. Wisconsin is probably the definitive online reference.
- Decision Tree for optimization software, by Mittelman and Spellucci, with emphasis on noncommercial software. Includes much explanation!
- Guide to available mathematical software (GAMS), run by NIST, similar to the Mittelman site but with less discussion. You browse by taxonomy.
- Optimization online pre-print server; also has email list. Many people post both here and to the very popular arXiv.
- MetaOptimize looks interesting; haven't yet explored it in detail
- wikimization, a "repository and resource for all things Optimization", in wiki style. Has wiki articles on some optimization subjects, and also short bios of researchers, and some computer code examples.
- EE364b: Convex Optimization II Stanford class by Stephen Boyd. The webpage has lecture notes and links to more resources. A very nice resource.
- EE236C - Optimization Methods for Large-Scale Systems UCLA class by Lieven Vandenberghe. The webpage has very good lecture notes.
- Christoph Helmberg's website has information on optimization (IPM, survey papers, matrix recovery, polynomial optimization, etc.)
- The help files at YALMIP can be quite useful.