Zrinka has provided a well written and detailed writeup of her talk on sparse models for tracking time varying signals. You can read it here.

## Posts Tagged ‘Compressive Sensing’

### Tracking of time varying signals (Friday 10/22/2010)

November 28, 2010### Learning Sparse Graphical Models – Part 1 (Friday 11/05/2010)

November 5, 2010Ali began a discussion on learning the structure of sparse graphical models. The notes for the first lecture are attached. We will continue this discussion in a couple of weeks. The main reference he used was “High dimensional Ising model selection using ℓ1-regularized logistic regression.” by Ravikumar and Wainwright.

### Bayesian compressive sensing (Friday 10/15/2010)

October 19, 2010Ayan discussed “Compressive Sensing on Manifolds Using a Nonparametric Mixture of Factor Analyzers: Algorithm and Performance Bounds” by Chen. et. al. available here. This paper develops a Bayesian model for mixtures of factor analyzers in the framework of compressed sensing i.e. with sparsity constraints on the factors. This idea is used to model manifolds and related structures. The meeting notes are attached.

### Compressive Sensing (Friday 10/01/2010)

October 8, 2010Sanmi discussed “Bayesian Compressive Sensing via Belief Propagation” by Baron. et. al. available here, and discussed some other connections between probabilistic models and compressed sensing. The meeting notes are attached.

### Compressive Sensing (Friday 09/17/2010)

September 18, 2010Ali Jalali gave a great introduction to compressive sensing; presenting the general intuition and the main results. I have attached the meeting notes.