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» Training of Support Vector Machines with Mahalanobis Kernels
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NECO
2010
101views more  NECO 2010»
15 years 28 days ago
Large-Margin Classification in Infinite Neural Networks
We introduce a new family of positive-definite kernels for large margin classification in support vector machines (SVMs). These kernels mimic the computation in large neural netwo...
Youngmin Cho, Lawrence K. Saul
ICML
2008
IEEE
16 years 7 months ago
Robust matching and recognition using context-dependent kernels
The success of kernel methods including support vector machines (SVMs) strongly depends on the design of appropriate kernels. While initially kernels were designed in order to han...
Hichem Sahbi, Jean-Yves Audibert, Jaonary Rabariso...
CVPR
2010
IEEE
15 years 6 months ago
Robust RVM regression using sparse outlier model
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...
Kaushik Mitra, Ashok Veeraraghavan, Rama Chellappa
BIBE
2007
IEEE
142views Bioinformatics» more  BIBE 2007»
16 years 15 days ago
An HV-SVM Classifier to Infer TF-TF Interactions Using Protein Domains and GO Annotations
—Interactions between transcription factors (TFs) are necessary for deciphering the complex mechanisms of transcription regulation in eukaryotes. In this paper, we proposed a nov...
Xiaoli Li, Jun-Xiang Lee, Bharadwaj Veeravalli, Se...
AHS
2007
IEEE
219views Hardware» more  AHS 2007»
16 years 15 days ago
A learning machine for resource-limited adaptive hardware
Machine Learning algorithms allow to create highly adaptable systems, since their functionality only depends on the features of the inputs and the coefficients found during the tr...
Davide Anguita, Alessandro Ghio, Stefano Pischiutt...