5 search results - page 1 / 1 » Learning Preferences with Millions of Parameters by Enforcin... |
ICDM
2010
IEEE
13 years 2 months ago
2010
IEEE
We study the retrieval task that ranks a set of objects for a given query in the pairwise preference learning framework. Recently researchers found out that raw features (e.g. word...
ECML
2007
Springer
13 years 10 months ago
2007
Springer
We present a framework for efficient, accurate approximate Bayesian inference in generalized linear models (GLMs), based on the expectation propagation (EP) technique. The paramete...
IPMI
2011
Springer
12 years 8 months ago
2011
Springer
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...
CVPR
2006
IEEE
14 years 6 months ago
2006
IEEE
Shrinkage is a well known and appealing denoising technique. The use of shrinkage is known to be optimal for Gaussian white noise, provided that the sparsity on the signal's ...
KDD
2007
ACM
14 years 5 months ago
2007
ACM
The collaborative filtering approach to recommender systems predicts user preferences for products or services by learning past useritem relationships. In this work, we propose no...