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» Generalized Discriminant Analysis Using a Kernel Approach
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NIPS
2004
13 years 10 months ago
Maximum-Margin Matrix Factorization
We present a novel approach to collaborative prediction, using low-norm instead of low-rank factorizations. The approach is inspired by, and has strong connections to, large-margi...
Nathan Srebro, Jason D. M. Rennie, Tommi Jaakkola
ICPR
2004
IEEE
14 years 10 months ago
Tangent Vector Kernels for Invariant Image Classification with SVMs
This paper presents an application of the general sample-to-object approach to the problem of invariant image classification. The approach results in defining new SVM kernels base...
Alexei Pozdnoukhov, Samy Bengio
GECCO
2007
Springer
130views Optimization» more  GECCO 2007»
14 years 3 months ago
Variable discrimination of crossover versus mutation using parameterized modular structure
Recent work has provided functions that can be used to prove a principled distinction between the capabilities of mutation-based and crossover-based algorithms. However, prior fun...
Rob Mills, Richard A. Watson
ISNN
2009
Springer
14 years 3 months ago
Nonlinear Component Analysis for Large-Scale Data Set Using Fixed-Point Algorithm
Abstract. Nonlinear component analysis is a popular nonlinear feature extraction method. It generally uses eigen-decomposition technique to extract the principal components. But th...
Weiya Shi, Yue-Fei Guo
ICIAP
2009
ACM
13 years 6 months ago
Video Event Classification Using Bag of Words and String Kernels
Abstract. The recognition of events in videos is a relevant and challenging task of automatic semantic video analysis. At present one of the most successful frameworks, used for ob...
Lamberto Ballan, Marco Bertini, Alberto Del Bimbo,...