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CVPR
2010
IEEE
14 years 9 days ago
Large-Scale Image Categorization with Explicit Data Embedding
Kernel machines rely on an implicit mapping of the data such that non-linear classification in the original space corresponds to linear classification in the new space. As kernel ...
Florent Perronnin, Jorge Sanchez, Yan Liu
KDD
2008
ACM
181views Data Mining» more  KDD 2008»
14 years 9 months ago
Learning subspace kernels for classification
Kernel methods have been applied successfully in many data mining tasks. Subspace kernel learning was recently proposed to discover an effective low-dimensional subspace of a kern...
Jianhui Chen, Shuiwang Ji, Betul Ceran, Qi Li, Min...
ATAL
2010
Springer
13 years 9 months ago
Inter-robot transfer learning for perceptual classification
We introduce the novel problem of inter-robot transfer learning for perceptual classification of objects, where multiple heterogeneous robots communicate and transfer learned obje...
Zsolt Kira
BMCBI
2006
173views more  BMCBI 2006»
13 years 9 months ago
Kernel-based distance metric learning for microarray data classification
Background: The most fundamental task using gene expression data in clinical oncology is to classify tissue samples according to their gene expression levels. Compared with tradit...
Huilin Xiong, Xue-wen Chen
ICMLC
2010
Springer
13 years 7 months ago
A comparative study on two large-scale hierarchical text classification tasks' solutions
: Patent classification is a large scale hierarchical text classification (LSHTC) task. Though comprehensive comparisons, either learning algorithms or feature selection strategies...
Jian Zhang, Hai Zhao, Bao-Liang Lu