79 search results - page 1 / 16 » Projected Subgradient Methods for Learning Sparse Gaussians |
UAI
2008
13 years 6 months ago
2008
Gaussian Markov random fields (GMRFs) are useful in a broad range of applications. In this paper we tackle the problem of learning a sparse GMRF in a high-dimensional space. Our a...
COLT
2010
Springer
13 years 2 months ago
2010
Springer
We present a new family of subgradient methods that dynamically incorporate knowledge of the geometry of the data observed in earlier iterations to perform more informative gradie...
ATAL
2010
Springer
13 years 5 months ago
2010
Springer
Many applications in multiagent learning are essentially convex optimization problems in which agents have only limited communication and partial information about the function be...
ICML
2007
IEEE
14 years 5 months ago
2007
IEEE
We describe and analyze a simple and effective iterative algorithm for solving the optimization problem cast by Support Vector Machines (SVM). Our method alternates between stocha...
CORR
2012
Springer
12 years 15 days ago
2012
Springer
We study the problem of learning high dimensional regression models regularized by a structured-sparsity-inducing penalty that encodes prior structural information on either input...