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» Support Vector Machines for Camera Calibration Problem
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ICPR
2010
IEEE
13 years 11 months ago
Fast Training of Object Detection Using Stochastic Gradient Descent
Training datasets for object detection problems are typically very large and Support Vector Machine (SVM) implementations are computationally complex. As opposed to these complex ...
Rob Wijnhoven, Peter H. N. De With
NIPS
2007
13 years 10 months ago
Multi-Task Learning via Conic Programming
When we have several related tasks, solving them simultaneously is shown to be more effective than solving them individually. This approach is called multi-task learning (MTL) and...
Tsuyoshi Kato, Hisashi Kashima, Masashi Sugiyama, ...
NIPS
2004
13 years 10 months ago
Maximum Margin Clustering
We propose a new method for clustering based on finding maximum margin hyperplanes through data. By reformulating the problem in terms of the implied equivalence relation matrix, ...
Linli Xu, James Neufeld, Bryce Larson, Dale Schuur...
IJON
2006
87views more  IJON 2006»
13 years 9 months ago
Translation-invariant classification of non-stationary signals
Non-stationary signal classification is a complex problem. This problem becomes even more difficult if we add the following hypothesis: each signal includes a discriminant wavefor...
Vincent Guigue, Alain Rakotomamonjy, Stépha...
PAMI
2010
192views more  PAMI 2010»
13 years 7 months ago
Multiway Spectral Clustering with Out-of-Sample Extensions through Weighted Kernel PCA
—A new formulation for multiway spectral clustering is proposed. This method corresponds to a weighted kernel principal component analysis (PCA) approach based on primal-dual lea...
Carlos Alzate, Johan A. K. Suykens