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» Variational Relevance Vector Machines
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JMLR
2008
133views more  JMLR 2008»
13 years 7 months ago
Algorithms for Sparse Linear Classifiers in the Massive Data Setting
Classifiers favoring sparse solutions, such as support vector machines, relevance vector machines, LASSO-regression based classifiers, etc., provide competitive methods for classi...
Suhrid Balakrishnan, David Madigan
EMNLP
2009
13 years 5 months ago
Reverse Engineering of Tree Kernel Feature Spaces
We present a framework to extract the most important features (tree fragments) from a Tree Kernel (TK) space according to their importance in the target kernelbased machine, e.g. ...
Daniele Pighin, Alessandro Moschitti
IROS
2006
IEEE
136views Robotics» more  IROS 2006»
14 years 1 months ago
Panoramic View-Based Navigation in Outdoor Environments Based on Support Vector Learning
— This paper describes a panoramic view-based navigation in outdoor environments. We have been developing a two-phase navigation method. In the training phase, the robot acquires...
Hideo Morita, Michael Hild, Jun Miura, Yoshiaki Sh...
NIPS
2001
13 years 8 months ago
Covariance Kernels from Bayesian Generative Models
We propose the framework of mutual information kernels for learning covariance kernels, as used in Support Vector machines and Gaussian process classifiers, from unlabeled task da...
Matthias Seeger
ESANN
2006
13 years 9 months ago
Efficient Forward Regression with Marginal Likelihood
We propose an efficient forward regression algorithm based on greedy optimization of marginal likelihood. It can be understood as a forward selection procedure which adds a new bas...
Ping Sun, Xin Yao