711 search results - page 72 / 143 » Applying Support Vector Machines to Imbalanced Datasets |
GPEM
2008
13 years 10 months ago
2008
In this work a cooperative, bid-based, model for problem decomposition is proposed with application to discrete action domains such as classification. This represents a significan...
ECML
2006
Springer
14 years 1 months ago
2006
Springer
In this paper, we provide a study on the use of tree kernels to encode syntactic parsing information in natural language learning. In particular, we propose a new convolution kerne...
ICASSP
2011
IEEE
13 years 1 months ago
2011
IEEE
This paper presents a novel method for reducing the dimensionality of kernel spaces. Recently, to maintain the convexity of training, loglinear models without mixtures have been u...
CIDM
2007
IEEE
14 years 2 months ago
2007
IEEE
Kernel methods are effective approaches to the modeling of structured objects in learning algorithms. Their major drawback is the typically high computational complexity of kernel ...
CVPR
2010
IEEE
13 years 10 months ago
2010
IEEE
Kernel regression techniques such as Relevance Vector Machine (RVM) regression, Support Vector Regression and Gaussian processes are widely used for solving many computer vision p...