362 search results - page 1 / 73 » Analysis and Generalizations of the Linearized Bregman Metho... |
SIAMIS
2010
12 years 11 months ago
2010
This paper analyzes and improves the linearized Bregman method for solving the basis pursuit and related sparse optimization problems. The analysis shows that the linearized Bregma...
SDM
2004
SIAM
13 years 5 months ago
2004
SIAM
A wide variety of distortion functions, such as squared Euclidean distance, Mahalanobis distance, Itakura-Saito distance and relative entropy, have been used for clustering. In th...
COMPUTING
2007
13 years 4 months ago
2007
In this paper we consider error estimation for image restoration problems based on generalized Bregman distances. This error estimation technique has been used to derive convergen...
ISAAC
2009
Springer
13 years 11 months ago
2009
Springer
The k-means algorithm is the method of choice for clustering large-scale data sets and it performs exceedingly well in practice. Most of the theoretical work is restricted to the c...
JMLR
2010
13 years 2 months ago
2010
The problem of computing a maximum a posteriori (MAP) configuration is a central computational challenge associated with Markov random fields. There has been some focus on “tr...