(Update: Feb 10 2012. Please you find broken links, please kindly drop me an email at sunjunus @ gmail.com)
Dedicated research websites of interest
- Compressive sensing 2.0 community (the universe of compressive sensing)
- Compressive sensing resources (Rice DSP)
- Low-rank matrix recovery and completion via convex optimization (Prof. Yi Ma’s research page)
- The similarity search wiki
- Optic Flow , Stereo, MView, MRF Evaluation (Middle-Bury)
- Deep Learning
- Kernel Machines (not quite up-to-date, mostly before 2009)
- Minimal Problems in Computer Vision (Geometric vision and algebraic equations)
- Gaussian Processes Website
Events/Workshops/Tutorials of interest
- CVPR Tutorials (2012, 2011, 2010, 2009, 2008, 2007, 2006)
- ICCV Tutorials (2011, 2009, 2007)
- ECCV Tutorials (2012, 2010, 2008, 2006)
- ICML Tutorials (2012, 2011, 2010, 2009, 2008, 2007, 2006)
- NIPS Tutorials (2012, 2011, 2010, 2009, 2008, 2007, 2006)
- STOC Programs (2011, 2010, 2009, 2008., 2007, 2006)
- FOCS Programs (2011, 2010, 2009, 2008, 2007, 2006)
- COLT Programs (2011, 2010, 2009, 2008, 2007, 2006)
- International Workshop on Optimization for Machine Learning (2011, 2010, 2009, 2008, in conjunction with NIPS).
- Workshop on Low-Rank Methods for Large-Scale Machine Learning. (2011, 2010, in conjunction with NIPS).
- Workshop on Discrete Optimization in Machine Learning. (2010, 2009, in conjunction with NIPS).
- Workshop on Transfer Learning via Rich Generative Models. (2010, in conjunction with NIPS).
- AAAI Fall Symposium on Manifold Learning and Its Applications (2010, 2009).
- SPARS Workshop: Signal Processing with Adaptive Sparse Structured Representations (2011, 2009, 2007, 2005).
- Duke Workshop on Sensing and Analysis of High-Dimensional Data (2011, 2009).
- Frontiers in Computer Vision (Organized by Alan Yuille and Aude Oliva, Aug 2011)
- Statistical Theory and Methods for Complex, High-Dimensional Data (Program at the Isaac Newton Institute for Mathematical Sciences, Cambridge U.)
- Tutorial on Compressive Sensing (Candes and others at LMS Invited Lecturer Series 2011, Cambridge U)
- SMALL workshop on sparse dictionary learning (Jan 2011).
- Modern trends in optimization and its application (Sep — Dec 2010, UCLA IPAM Long-term program)
- Machine learning summer school on theory and practice of computational learning (2009, Ohio State U, U. Chicago, TTI-C)
- 2nd International summer school on numerical linear algebra (2010, Gene Golub SIAM summer school 2010, Italy)
- Workshop on Algorithms for Modern Massive Data Sets (2012, 2010, 2008, 2006)
- Laplacian eigenvalues and eigenfunctions: theory, computation, application (UCLA IPAM Workshop, 2009)
- Prof. Yi Ma’s course on compressive sensing (UIUC, 2008 fall)
- Graph cuts and related discrete or continuous optimization problems (UCLA IPAM workshop, 2008).
- Compressive sensing and frontiers in signal processing (2007, UMN)
- 25 Years of RANSAC (2006, CVPR Workshop)
- Intelligent extraction of information from graphs and high dimensional data (UCLA IPAM Graduate Summer School, 2005)
Wonderful reference books and notes that are online
- Convex optimization (Boyd and Vandenberghe)
- Robust optimization (Ben-Tal, Ghaoui, Nemirovski)
- The elements of statistical learning: data mining, inference, and prediction (Hastie, Tibshirani and Friedman)
- Computer vision: algorithms and applications (Richard Szeliski)
- The quest for artificial intelligence: a history of ideas and achievements (Nils J. Nilsson)
- Artificial intelligence: Foundations of Computational Agents (David Poole and Alan Mackworth)
- Theoretical Foundation and Numerical Methods for Sparse Recovery (Ed. Fornasier, Massimo. Amongst the first volumes devoted to the subject of compressive sensing. Individual parts kindly released by their respective authors)
- Compressive Sensing and Structured Random Matrices (by Holger Rauhut)
- Numerical Methods for Sparse Recovery (by Massimo Fornasier)
- Sparse Recovery in Inverse Problems (by Ronny Ramlau and Gerd Teschke)
- An Introduction to Total Variation for Image Analysis (by Antonin Chambolle etc)
- ** Sparse and Redundant Representations: From Theory to Applications in Signal and Image Processing (Michael Elad. ** if you have Springer Link access. Among the first volumes devoted to the subject of compressive sensing. )
- Probability: Theory and Examples (by Richard Durrent)
- Information Theory, Inference, and Learning Algorithms (by David Mackay)
- Gaussian Processes for Machine Learning (by Carl Edward Rasmussen and Christopher K. I. Williams)
- ** Foundations and Trends in Computer Graphics and Vision, Machine Learning, Robotics, Signal Processing, Communications and Information Theory, Theoretical Computer Science (Not open -access in general, but you can obtain most survey articles there via Google research… )
- Hand of Mathematical Functions (Abramowitz and Stegun)