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• The project SMALL
  • Objectives
  • Partners
    • INRIA
    • University of Edinburgh
    • Queen Mary University of London
    • EPFL
    • TECHNION
  • Project ID
• Key Results
  • Cosparsity
  • Learning analysis operators
  • Learning structures
  • Dictionary Learning Theory
  • Compressible priors
  • Audio Inpainting
  • Spread Spectrum
  • Graph Wavelets
  • SMALLBox
• Software for reproducibility
  • SMALLbox
  • K-SVD
  • The Matching Pursuit ToolKit (MPTK)
  • Audio Inpainting toolbox
  • GAPn code
• SMALL Events
• Publications
• Intranet
  • Web site information
  • Mailing lists information
  • Forge information
  • Contractual documents
    • Grant Agreement
    • Description of Work (DoW)
    • Grant Agreement Annex II General Conditions
    • Consortium Agreement
    • DOW v2.0
  • Meetings
    • Videoconferences
    • 2009/03/25-26 Kick-off meeting
    • 2009/09/24-25 London meeting
    • 2010/02/09-12 Villars meeting
    • 2010/03/29-30 Review meeting
    • 2010/10/11-15 Jerusalem workshop
    • 2011/04/11-14 Second review meeting
    • 2012/06/23-26 Workshop + 3rd Review
  • Reports
    • Project management and report templates under FP7 projects
    • Quarterly reports
    • Annual reports
    • Final report
  • Deliverables
    • D0.1 Web site
    • D1.1 Review of algorithms for application to large scale data
    • D1.2 Proposed Algorithms for Structured Sparse Approximations and Available Open Source Softwares
    • D2.1 First report and open source
    • D2.2 Final Report and Open Source Software on Proposed Algorithms for Dictionary Learning
    • D3.1Report on Learning Structured Sparse Models
    • D3.2Report on Discovering Structure within Dictionary Learning
    • D3.3 Final report and open source software on learning
    • D3.4 Report and open source software on Multi-streamMulti-modal dictionary learning
    • D4.1 Report on theoretical aspects of sparse approximation
    • D4.2 Report on dictionary learning theory
    • D5.1 Evaluation framework design - D5.2 Initial release
    • D5.3 Evaluation/demonstration framework: final release
    • 6.1 First Workshop
    • D6.3 Final Workshop
    • template - deliverable
  • Project monitoring
    • Project activity matrix
    • Activity reports
    • Backup
  • Brainstorming
    • Analysis vs. synthesis sparse models
    • SMALL text book
    • Inpainting in audio and video
  • Glossary
  • Other events
    • ICASSP 2011
    • Sparse and Low Rank Approximation
    • Seminar at Schloss Dagstuhl
    • NIPS 2010
    • LVA/ICA 2010
    • Symposium at ICNAAM 2010
    • INSPIRE 2010
    • CSSIP 10
    • EUSIPCO 2010
    • Summer school at Hólar
    • Workshop at RICAM
    • Workshop at Hausdorff
    • 7th International Conference on Curves and Surfaces
  • Logo
    • Proposals
    • Header
    • Small header (pdf)
    • Small header (psd)
    • Small logo (eps)
    • Small logo (pdf)
  • OLD WEBSITE
    • Partners
    • SMALL project
    • Objectives
    • Links
    • Other events on Sparse Representations
    • Partners
• SMALL 2011 London Workshop
  • Videos of the talks
  • Slides of the talks
    • Opening Remarks - Mark Plumbley
    • Francis Bach - Structured sparsity-inducing norms through submodular functions
    • Mike Davies - Rank aware algorithms for joint sparse recovery
    • Holger Rauhut - Copressive sensing and structured random matrices
    • Pierre Vandergheynst - Transductive learning with spectral graph wavelets
    • Karin Schnass - Dictionary identification - Sparse matrix-factorization via L1-minimization
    • John Wright - Dictionary learning via L1-minimization: well-posedness and correct recovery
    • Michael Elad - Exploiting statistical dependencies in sparse representations
    • Kjersti Engan - Dictionary learning by RLA-DLA with applications
  • Posters of the Workshop
    • Andrew Thompson and Coralia Cartis - A new recovery analysis of Iterative Hard Thresholding
    • Felix Krahmer and Rachel Ward - New and improved Johnson-Lindenstrauss embeddings via the Restricted Isometry Property
    • Mohammad Golbabaei, Simon Arberet, Pierre Vandergheynst - Distributed Compressed Sensing of Hyperspectral images via Blind Source Separation
    • Daniele Barchiesi and Mark Plumbley - Dictionary Learning of Convolved Signals
    • Ivan Damnjanovic, Matthew Davies and Mark D. Plumbley - Sparse Representations and Dictionary Learning Evaluation Framework – SMALLbox
    • Michael E. Davies, Michael Elad, Raja Giryes, Rémi Gribonval, and Sangnam Nam - Cosparse Analysis Modeling
    • SMALL Project Overview
    • Amir ADLER, Valentin EMIYA, Maria JAFARI, Michael ELAD, Rémi GRIBONVAL, Mark PLUMBLEY - Audio inpainting: problem statement, relation with sparse representations and some experiments
    • Aris Gretsistas and Mark D. Plumbley - Approximate Conjugate Gradient Polytope Faces Pursuit for large scale sparse recovery problems
    • Andrew Nesbit and Mark Plmubley - Passive Acoustic Monitoring of Marine Mammals using Sparse Representations
    • Ken O'Hanlon and Mark D.Plumbley - Structured Non-negative Dictionary Learning for Music Transcription
  • Photos from workshop
• Workshop on Sparsity, Localization and Dictionary Learning