2631 search results - page 10 / 527 » A Practical Method for the Sparse Resultant |
JMLR
2012
11 years 10 months ago
2012
We develop scalable algorithms for regular and non-negative matrix completion. In particular, we base the methods on trace-norm regularization that induces a low rank predicted ma...
ICASSP
2011
IEEE
12 years 11 months ago
2011
IEEE
The 2- 1 sparse signal minimization problem can be solved efficiently by gradient projection. In many applications, the signal to be estimated is known to lie in some range of va...
ICDM
2010
IEEE
13 years 5 months ago
2010
IEEE
Abstract--Randomization is a general technique for evaluating the significance of data analysis results. In randomizationbased significance testing, a result is considered to be in...
ICDM
2009
IEEE
14 years 2 months ago
2009
IEEE
—We describe parallel methods for solving large-scale, high-dimensional, sparse least-squares problems that arise in machine learning applications such as document classificatio...
SIAMMAX
2010
13 years 2 months ago
2010
In this paper, we consider estimating sparse inverse covariance of a Gaussian graphical model whose conditional independence is assumed to be partially known. Similarly as in [5],...