About
Sparse estimation (or sparse recovery) is playing an increasingly important role in the statistics and machine learning communities. Several methods have recently been developed in both fields, which rely upon the notion of sparsity (e.g. penalty methods like the Lasso, Dantzig selector, etc.). Many of the key theoretical ideas and statistical analysis of the methods have been developed independently, but there is increasing awareness of the potential for cross-fertilization of ideas between statistics and machine learning.
Furthermore, there are interesting links between lasso-type methods and boosting (particularly, LP-boosting); there has been a renewed interest in sparse Bayesian methods. Sparse estimation is also important in unsupervised method (sparse PCA, etc.). Recent machine learning techniques for multi-task learning and collaborative filtering have been proposed which implement sparsity constraints on matrices (rank, structured sparsity, etc.). At the same time, sparsity is playing an important role in various application fields, ranging from image and video reconstruction and compression, to speech classification, text and sound analysis, etc.
The overall goal of the workshop is to bring together machine learning researchers with statisticians working on this timely topic of research, to encourage exchange of ideas between both communities and discuss further developments and theoretical underpinning of the methods.
For detailed information visit the Workshops website.
Videos

Latent Variable Sparse Bayesian Models
May 6, 2009
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5710 views

Some results for the adaptive Lasso
May 6, 2009
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6976 views

Testing and estimation in a sparse normal means model, with connections to shape...
May 6, 2009
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2883 views

High-Dimensional Non-Linear Variable Selection through Hierarchical Kernel Learn...
May 6, 2009
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4394 views

Distilled Sensing: Active sensing for sparse recovery
May 6, 2009
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4799 views

Phase transitions phenomenon in Compressed Sensing
May 6, 2009
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5391 views

Poster Spotlights 1
May 6, 2009
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3682 views

Learning with Many Reproducing Kernel Hilbert Spaces
May 6, 2009
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4426 views

Algorithmic Strategies for Non-convex Optimization in Sparse Learning
May 6, 2009
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7818 views

Matching Pursuit Kernel Fisher Discriminant Analysis
May 6, 2009
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3959 views

Sparsity in online multitask/multiview learning
May 6, 2009
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3207 views

Multi-Task Learning via Matrix Regularization
May 6, 2009
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3629 views

Sparse Exponential Weighting and Langevin Monte-Carlo
May 6, 2009
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3578 views

Large Precision Matrix Estimation for Time Series Data with Latent Factor Model
May 6, 2009
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4500 views

Fast methods for sparse recovery: alternatives to L1
May 6, 2009
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7312 views

Poster Spotlights 2
May 6, 2009
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3407 views