74 search results - page 2 / 15 » Learning sparse metrics via linear programming |
ICASSP
2010
IEEE
13 years 5 months ago
2010
IEEE
Given a set of data points drawn from multiple low-dimensional linear subspaces of a high-dimensional space, we consider the problem of clustering these points according to the su...
ICCV
2011
IEEE
12 years 4 months ago
2011
IEEE
Linear subspace learning (LSL) is a popular approach to image recognition and it aims to reveal the essential features of high dimensional data, e.g., facial images, in a lower di...
CORR
2010
Springer
13 years 3 months ago
2010
Springer
Gaussian graphical models are of great interest in statistical learning. Because the conditional independencies between different nodes correspond to zero entries in the inverse c...
KDD
2010
ACM
13 years 6 months ago
2010
ACM
We consider the problem of learning incoherent sparse and lowrank patterns from multiple tasks. Our approach is based on a linear multi-task learning formulation, in which the spa...
JMLR
2010
12 years 11 months ago
2010
This paper considers the problem of estimating a high dimensional inverse covariance matrix that can be well approximated by "sparse" matrices. Taking advantage of the c...