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ICPR
2008
IEEE
16 years 5 months ago
A discrete-time parallel update algorithm for distributed learning
We present a distributed machine learning framework based on support vector machines that allows classification problems to be solved iteratively through parallel update algorithm...
Christian Bauckhage, Tansu Alpcan
NIPS
2007
15 years 5 months ago
Active Preference Learning with Discrete Choice Data
We propose an active learning algorithm that learns a continuous valuation model from discrete preferences. The algorithm automatically decides what items are best presented to an...
Eric Brochu, Nando de Freitas, Abhijeet Ghosh
ICML
2010
IEEE
15 years 5 months ago
Multi-Task Learning of Gaussian Graphical Models
We present multi-task structure learning for Gaussian graphical models. We discuss uniqueness and boundedness of the optimal solution of the maximization problem. A block coordina...
Jean Honorio, Dimitris Samaras
CVPR
2010
IEEE
16 years 8 days ago
Safety in Numbers: Learning Categories from Few Examples with Multi Model Knowledge Transfer
Learning object categories from small samples is a challenging problem, where machine learning tools can in general provide very few guarantees. Exploiting prior knowledge may be ...
Tatiana Tommasi, Francesco Orabona, Barbara Caputo
MICCAI
2005
Springer
15 years 9 months ago
Learning Best Features for Deformable Registration of MR Brains
Abstract. This paper presents a learning method to select best geometric features for deformable brain registration. Best geometric features are selected for each brain location, a...
Guorong Wu, Feihu Qi, Dinggang Shen