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» Algorithms for Learning Kernels Based on Centered Alignment
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ECCV
2008
Springer
16 years 7 months ago
Face Alignment Via Component-Based Discriminative Search
In this paper, we propose a component-based discriminative approach for face alignment without requiring initialization1 . Unlike many approaches which locally optimize in a small ...
Lin Liang, Rong Xiao, Fang Wen, Jian Sun
ICML
2005
IEEE
16 years 6 months ago
Semi-supervised graph clustering: a kernel approach
Semi-supervised clustering algorithms aim to improve clustering results using limited supervision. The supervision is generally given as pairwise constraints; such constraints are...
Brian Kulis, Sugato Basu, Inderjit S. Dhillon, Ray...
EEE
2005
IEEE
15 years 11 months ago
Learning the Kernel Matrix for XML Document Clustering
The rapid growth of XML adoption has urged for the need of a proper representation for semi-structured documents, where the document structural information has to be taken into ac...
Jianwu Yang, William Kwok-Wai Cheung, Xiaoou Chen
CVPR
2010
IEEE
15 years 6 months ago
Learning kernels for variants of normalized cuts: Convex relaxations and applications
We propose a new algorithm for learning kernels for variants of the Normalized Cuts (NCuts) objective – i.e., given a set of training examples with known partitions, how should ...
Lopamudra Mukherjee, Vikas Singh, Jiming Peng, Chr...
TNN
2010
176views Management» more  TNN 2010»
15 years 17 days ago
Sparse approximation through boosting for learning large scale kernel machines
Abstract--Recently, sparse approximation has become a preferred method for learning large scale kernel machines. This technique attempts to represent the solution with only a subse...
Ping Sun, Xin Yao