First Andrew had a post on Uncompressing the concept of compressed sensing go read it and post a comment there if you feel inclined, I'll wait.
The Statistical physics, Optimization, Inference and Message-Passing algorithms School at Les Houches ended on October 11, 2013, here are the presentations for some of the speakers as well the titles of posters. I am told that notes were taken and they would be made available in the future. Stay tuned, in the meantime:
List of lecturers:First week:
- Cris Moore (Santa Fe Institute): The nature of computation.
- Andrea Montanari (Stanford Univ.): Denoising, compressed sensing and low-rank approximation.
- Giorgio Parisi (La Sapienza Roma): Replica theory and spin glasses
- Devavrat Shah (MIT): Statistical inference with probabilistic graphical models.
Second week:
- Marc Mezard (ENS Paris): Cavity method: message passing from a physics perspective.
- Andrea Montanari (Stanford Univ.): idem...
- Riccardo Zecchina (Politecnico Torino): Cavity approaches for stochastic optimisation and inverse dynamical problems.
- Manfred Opper (Berlin Univ.): Expectation-propagation and topics in inference.
- Rudiger Urbanke (EPFL): Error correcting codes and spatial coupling
- Amin Coja-Oghlan (Frankfurt Univ.): Phase transitions in random discrete structures: a rigorous approach
- David Gamarnik (MIT) : Local Algorithms for Random Networks.
List of posters:Tuesday:1. Marco Mondelli: Scaling Exponent of List Decoders with Applications to Polar Codes2. Andrei Giurgiu: A proof of the exactness of the replica symmetric formula for LDPC codes above the MAP threshold.3. El-Khatib Rafah: Displacement Convexity - A Framework for the Analysis of Spatially Coupled Codes4. Santhosh Kumar Vanaparthy: Threshold Saturation for Spatially-Coupled LDPC and LDGM Codes on BMS Channels5. Hamed Hassani: New lower bounds for CSPs using spatial coupling6. Jean Barbier: Robust error correction for real-valued signals via message-passing decoding and spatial coupling7. Francesco Caltagirone: Dynamics and termination cost of spatially coupled mean-field models8. Cohen Or: Low temperature expansion of steady-state measures of nonequilibrium markov chains via graphical representatio9. Aurelien Decelle: Belief Propagation inspired Monte Carlo10. Yuji Sakai: Markov Chain Monte Carlo Method with Skew Detailed Balance Condition11. Satoshi Takabe: Typical behavior of the linear programming method for combinatorial optimization problems12. Masahiko Ueda: Calculation of 1RSB transition temperature of spin glass models on regular random graphs under replica symmetric ansatz13. Wang Chuang: Tensor renormalization group method for spin glass14. Gino Del Ferraro: Mean field spin glasses treated with PDE techniques15. Flaviano Morone: Large deviations of correlation functions in random magnets16. Andre Manoel: Statistical mechanics for the analysis and design of information hiding algorithms17. Ayaka Sakata: Time evolution of autocorrelation function in dynamical replica theory18. Alexander Mozeika: Projected generalized free energies for non-equilibrium states19. Stefan Falkner: A Renormalization Group Approach to Quantum Walks20. Moffatt, Iain: The Potts-Tutte connection in an external fieldWednesday:21. Jonas Dittmann: TV regularized tomographic reconstruction from few (X-Ray) projections based on CS22. Yingying Xu: Statistical Mechanics Approach to 1-Bit Compressed Sensing.23. Christophe Schulke: Blind Calibration in Compressed Sensing using Message Passing Algorithms24. Wang Chuang: Partition function expansion for generalized belief propagation.25. Harrison Elizabeth: Probabilistic Control in Smart-Grids.26. Maksym Girnyk: A Statistical Mechanical Approach to MIMO Channels27. Ulugbek Kamilov: Wavelet-Domain Approximate Message Passing for Bayesian Image Deconvolution28. Rémi Lemoy: Variable-focused local search on Random 3-SAT29. Alberto Guggiola: Mapping between sequence and response space in the olfactory system in Drosophila30. Marcus Benna: Long-term memory with bounded synaptic weights31. Or Zuk: TBA32. Jack Raymond: Utilizing the Hessian to improve variational inference33. Andrey Lokhov: Dynamic message-passing equations and application to inference of epidemic origin34. Aurelien Decelle: Decimation based method to improve inference using the Pseudo-Likelihood method35. Alejandro Lage Castellanos: TBA36. Munik Shrestha: Spread of reinforcement driven trends in networks with message-passing approach37. Dani Martí: Scalability properties of multimodular networks with dynamic gating38. Abigail Zoe Jacobs: Latent space models for network structure: an application to ecology39. Shunsuke Watanabe: The analysis of degree-correlated networks based on cavity method40. Caterina De Bacco: Shortest non-overlapping routes on random graphs.
The DFG/SNF Research Group FOR916 and the DFG Research Training Group 1023 organizes a workshop on Statistical Issues in Compressive Sensing at the University of Göttingen, Germany, November 11-13, 2013. The list of abstract is below:
- Timo Aspelmeier Universität Göttingen Abstract
- Emmanuel Candès Standford University Abstract
- Rui Castro TU Eindhoven Abstract
- Volkan Cevher Ecole Polytechnique Fédérale de Lausanne Abstract
- David Groß Universität Freiburg
- Markus Haltmeier Universität Insbruck Abstract
- Holger Kösters Universität Bielefeld Abstract
- Florent Krzakala Ecole Normale Superieure, Paris Abstract
- Gitta Kutyniok TU Berlin Abstract
- Guillaume Lecué Université Paris-Est - Marne-la-vallée Abstract
- Holger Rauhut RTWH Aachen Abstract
- Rayan Saab UC San Diego Abstract
- Jared Tanner Oxford University
- Sara van de Geer ETH Zürich Abstract
- Yves Wiaux Heriot-Watt University Edinburgh
Image Credit: NASA/JPL/Space Science Institute
N00217830.jpg was taken on October 21, 2013 and received on Earth October 22, 2013. The camera was pointing toward SATURN-DRING at approximately 1,463,952 miles (2,356,003 kilometers) away, and the image was taken using the CL1 and CL2 filters.
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Liked this entry ? subscribe to Nuit Blanche's feed, there's more where that came from. You can also subscribe to Nuit Blanche by Email, explore the Big Picture in Compressive Sensing or the Matrix Factorization Jungle and join the conversations on compressive sensing, advanced matrix factorization and calibration issues on Linkedin.
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