Optimization for Sparse Estimation

Saturday, June 22, 2013 - 9:00am - 10:30am
Lind 305
Julien Mairal (INRIA )
We will discuss practical optimization algorithms for estimating sparse models,
both from a statistics and a signal processing point of view. First, we will
cover non-convex optimization techniques such as greedy algorithms and
DC-programming. Second, we will focus on convex optimization: first-order
methods, iterative reweighted least squares, and the homotopy method for the

[1] Bach, F., Jenatton, R., Mairal, J., & Obozinski, G. (2012). Optimization
with sparsity-inducing penalties.Foundations and Trends in Machine Learning,
4(1), 1--106, 2012.