165 search results - page 14 / 33 » Algorithms for Sparse Linear Classifiers in the Massive Data... |
CVPR
2004
IEEE
14 years 9 months ago
2004
IEEE
We consider the problem of clustering data lying on multiple subspaces of unknown and possibly different dimensions. We show that one can represent the subspaces with a set of pol...
ICPR
2008
IEEE
14 years 1 months ago
2008
IEEE
We propose a new transductive learning algorithm for learning optimal linear representations that utilizes unlabeled data. We pose the problem of learning linear representations a...
HIS
2004
13 years 8 months ago
2004
Boosting is a general method for improving the accuracy of a learning algorithm. AdaBoost, short form for Adaptive Boosting method, consists of repeated use of a weak or a base le...
KDD
2008
ACM
14 years 7 months ago
2008
ACM
We address the problem of classification in partially labeled networks (a.k.a. within-network classification) where observed class labels are sparse. Techniques for statistical re...
KDD
2010
ACM
13 years 9 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...