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» Learning low-rank kernel matrices
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NIPS
2007
13 years 8 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
GIS
2010
ACM
13 years 5 months ago
Kernelized map matching
Map matching is a fundamental operation in many applications such as traffic analysis and location-aware services, the killer apps for ubiquitous computing. In the past, several m...
Ahmed Jawad, Kristian Kersting
ICPR
2010
IEEE
14 years 2 months ago
Semi-Supervised Distance Metric Learning by Quadratic Programming
This paper introduces a semi-supervised distance metric learning algorithm which uses pair-wise equivalence (similarity and dissimilarity) constraints to improve the original dist...
Hakan Cevikalp
ICML
2004
IEEE
14 years 7 months ago
Online and batch learning of pseudo-metrics
We describe and analyze an online algorithm for supervised learning of pseudo-metrics. The algorithm receives pairs of instances and predicts their similarity according to a pseud...
Shai Shalev-Shwartz, Yoram Singer, Andrew Y. Ng
CVPR
2010
IEEE
13 years 5 months ago
Visual classification with multi-task joint sparse representation
We address the problem of computing joint sparse representation of visual signal across multiple kernel-based representations. Such a problem arises naturally in supervised visual...
Xiaotong Yuan, Shuicheng Yan