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» Kernels for Semi-Structured Data
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149
Voted
CVPR
2009
IEEE
15 years 4 months ago
Nonlinear Nonnegative Component Analysis
In this paper general solutions for Nonlinear Nonnegative Component Analysis for data representation and recognition are proposed. That is, motivated by a combination of the Nonne...
Stefanos Zafeiriou, Maria Petrou
95
Voted
NIPS
2007
15 years 2 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
104
Voted
AAAI
2000
15 years 2 months ago
Interactive Training for Synthetic Characters
Compelling synthetic characters must behave in ways that reflect their past experience and thus allow for individual personalization. We therefore need a method that allows charac...
Song-Yee Yoon, Robert C. Burke, Bruce Blumberg, Ge...
111
Voted
ICCV
2009
IEEE
1022views Computer Vision» more  ICCV 2009»
16 years 6 months ago
Kernelized Locality-Sensitive Hashing for Scalable Image Search
Fast retrieval methods are critical for large-scale and data-driven vision applications. Recent work has explored ways to embed high-dimensional features or complex distance fun...
Brian Kulis, Kristen Grauman
122
Voted
ICIP
2005
IEEE
16 years 2 months ago
Visual tracking via efficient kernel discriminant subspace learning
Robustly tracking moving objects in video sequences is one of the key problems in computer vision. In this paper we introduce a computationally efficient nonlinear kernel learning...
Chunhua Shen, Anton van den Hengel, Michael J. Bro...