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JMLR
2010
121views more  JMLR 2010»
13 years 5 months ago
Sparse Semi-supervised Learning Using Conjugate Functions
In this paper, we propose a general framework for sparse semi-supervised learning, which concerns using a small portion of unlabeled data and a few labeled data to represent targe...
Shiliang Sun, John Shawe-Taylor
CVPR
2010
IEEE
14 years 6 months ago
Parallel Graph-cuts by Adaptive Bottom-up Merging
Graph-cuts optimization is prevalent in vision and graphics problems. It is thus of great practical importance to parallelize the graph-cuts optimization using today’s ubiquitou...
Jiangyu Liu, Jian Sun
ICML
2009
IEEE
14 years 11 months ago
Learning with structured sparsity
This paper investigates a new learning formulation called structured sparsity, which is a naturalextensionofthestandardsparsityconceptinstatisticallearningandcompressivesensing. B...
Junzhou Huang, Tong Zhang, Dimitris N. Metaxas
AI
1999
Springer
13 years 10 months ago
Learning by Discovering Concept Hierarchies
We present a new machine learning method that, given a set of training examples, induces a definition of the target concept in terms of a hierarchy of intermediate concepts and th...
Blaz Zupan, Marko Bohanec, Janez Demsar, Ivan Brat...
INFOCOM
2008
IEEE
14 years 4 months ago
Real-Time Video Multicast in WiMAX Networks
Abstract—IEEE 802.16e WiMAX is a promising new technology for broadband access networks. Amongst the class of applications that can be supported is real time video services (such...
Supratim Deb, Sharad Jaiswal, Kanthi Nagaraj