318 search results - page 4 / 64 » Learning subspace kernels for classification |
KDD
2007
ACM
14 years 8 months ago
2007
ACM
Typical approaches to multi-label classification problem require learning an independent classifier for every label from all the examples and features. This can become a computati...
KDD
2006
ACM
14 years 8 months ago
2006
ACM
Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...
ICIP
2005
IEEE
14 years 9 months ago
2005
IEEE
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...
ICASSP
2011
IEEE
12 years 11 months ago
2011
IEEE
We propose a kernelized maximal-figure-of-merit (MFoM) learning approach to efficiently training a nonlinear model using subspace distance minimization. In particular, a fixed,...
JMLR
2010
13 years 2 months ago
2010
Appropriate selection of the kernel function, which implicitly defines the feature space of an algorithm, has a crucial role in the success of kernel methods. In this paper, we co...