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» A DC-programming algorithm for kernel selection
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Book
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17 years 2 months ago
Gaussian Processes for Machine Learning
"Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning...
Carl Edward Rasmussen and Christopher K. I. Willia...
CIKM
2009
Springer
15 years 10 months ago
Incremental query evaluation for support vector machines
Support vector machines (SVMs) have been widely used in multimedia retrieval to learn a concept in order to find the best matches. In such a SVM active learning environment, the ...
Danzhou Liu, Kien A. Hua
3DIM
2005
IEEE
15 years 9 months ago
Gaussian Scale-Space Dense Disparity Estimation with Anisotropic Disparity-Field Diffusion
We present a new reliable dense disparity estimation algorithm which employs Gaussian scale-space with anisotropic disparity-field diffusion. This algorithm estimates edge-preserv...
Jangheon Kim, Thomas Sikora
ICML
2004
IEEE
16 years 4 months ago
Predictive automatic relevance determination by expectation propagation
In many real-world classification problems the input contains a large number of potentially irrelevant features. This paper proposes a new Bayesian framework for determining the r...
Yuan (Alan) Qi, Thomas P. Minka, Rosalind W. Picar...
JMLR
2011
148views more  JMLR 2011»
14 years 11 months ago
Multitask Sparsity via Maximum Entropy Discrimination
A multitask learning framework is developed for discriminative classification and regression where multiple large-margin linear classifiers are estimated for different predictio...
Tony Jebara