Other resources

From SparseSolver

See also textbooks.

Contents 1 Compressed sensing resources 2 Lists of solvers 3 Smaller and/or personal websites 4 Curated Technical Pages 5 Other wikis on related material 6 Blogs 7 Discussion Groups 8 Other Technical Pages 9 Wikipedia entries 10 Optimization resources

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
    • The Matrix Factorization Jungle Page

Other wikis on related material

• RecSysWiki is about everything related to recommender systems (as in the Netflix prize).

Blogs

• 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

• Discussion groups on LinkedIn (you need to join LinkedIn to be member of these groups]
  • The Compressive Sensing Study Group
  • The Matrix Factorization Group

Other Technical Pages

• Online Videos on Compressive Sensing by Igor Carron
• Learning Compressive Sensing by Igor Carron

Wikipedia entries

• Compressed Sensing

Optimization resources

• 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.