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MICCAI
2010
Springer
13 years 3 months ago
Multi-Class Sparse Bayesian Regression for Neuroimaging Data Analysis
The use of machine learning tools is gaining popularity in neuroimaging, as it provides a sensitive assessment of the information conveyed by brain images. In particular, finding ...
Vincent Michel, Evelyn Eger, Christine Keribin, Be...
IPMI
2011
Springer
12 years 8 months ago
Generalized Sparse Regularization with Application to fMRI Brain Decoding
Many current medical image analysis problems involve learning thousands or even millions of model parameters from extremely few samples. Employing sparse models provides an effecti...
Bernard Ng, Rafeef Abugharbieh
SDM
2007
SIAM
162views Data Mining» more  SDM 2007»
13 years 6 months ago
Probabilistic Joint Feature Selection for Multi-task Learning
We study the joint feature selection problem when learning multiple related classification or regression tasks. By imposing an automatic relevance determination prior on the hypo...
Tao Xiong, Jinbo Bi, R. Bharat Rao, Vladimir Cherk...
DAGM
2006
Springer
13 years 8 months ago
Model Selection in Kernel Methods Based on a Spectral Analysis of Label Information
Abstract. We propose a novel method for addressing the model selection problem in the context of kernel methods. In contrast to existing methods which rely on hold-out testing or t...
Mikio L. Braun, Tilman Lange, Joachim M. Buhmann
JMLR
2010
179views more  JMLR 2010»
12 years 11 months ago
PAC-Bayesian Analysis of Co-clustering and Beyond
We derive PAC-Bayesian generalization bounds for supervised and unsupervised learning models based on clustering, such as co-clustering, matrix tri-factorization, graphical models...
Yevgeny Seldin, Naftali Tishby