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» Learning subspace kernels for classification
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ICPR
2010
IEEE
13 years 5 months ago
Multiple Kernel Learning with High Order Kernels
Previous Multiple Kernel Learning approaches (MKL) employ different kernels by their linear combination. Though some improvements have been achieved over methods using single kerne...
Shuhui Wang, Shuqiang Jiang, Qingming Huang, Qi Ti...
NIPS
2003
13 years 9 months ago
Kernel Dimensionality Reduction for Supervised Learning
We propose a novel method of dimensionality reduction for supervised learning. Given a regression or classification problem in which we wish to predict a variable Y from an expla...
Kenji Fukumizu, Francis R. Bach, Michael I. Jordan
ICML
2006
IEEE
14 years 8 months ago
Learning a kernel function for classification with small training samples
When given a small sample, we show that classification with SVM can be considerably enhanced by using a kernel function learned from the training data prior to discrimination. Thi...
Tomer Hertz, Aharon Bar-Hillel, Daphna Weinshall
NIPS
2007
13 years 9 months ago
Discriminative K-means for Clustering
We present a theoretical study on the discriminative clustering framework, recently proposed for simultaneous subspace selection via linear discriminant analysis (LDA) and cluster...
Jieping Ye, Zheng Zhao, Mingrui Wu
CVPR
2005
IEEE
14 years 9 months ago
Local Discriminant Embedding and Its Variants
We present a new approach, called local discriminant embedding (LDE), to manifold learning and pattern classification. In our framework, the neighbor and class relations of data a...
Hwann-Tzong Chen, Huang-Wei Chang, Tyng-Luh Liu