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ECCV
2006
Springer
16 years 8 months ago
Efficient Belief Propagation with Learned Higher-Order Markov Random Fields
Belief propagation (BP) has become widely used for low-level vision problems and various inference techniques have been proposed for loopy graphs. These methods typically rely on a...
Xiangyang Lan, Stefan Roth, Daniel P. Huttenlocher...
197
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WSDM
2012
ACM
259views Data Mining» more  WSDM 2012»
14 years 2 months ago
Learning recommender systems with adaptive regularization
Many factorization models like matrix or tensor factorization have been proposed for the important application of recommender systems. The success of such factorization models dep...
Steffen Rendle
IJCNN
2006
IEEE
16 years 22 days ago
A Variational EM Approach to Predicting Uncertainty in Supervised Learning
— In many applications of supervised learning, the conditional average of the target variables is not sufficient for prediction. The dependencies between the explanatory variabl...
Markus Harva
IDA
2005
Springer
16 years 6 days ago
Bayesian Networks Learning for Gene Expression Datasets
DNA arrays yield a global view of gene expression and can be used to build genetic networks models, in order to study relations between genes. Literature proposes Bayesian network ...
Giacomo Gamberoni, Evelina Lamma, Fabrizio Riguzzi...
ESSMAC
2003
Springer
15 years 12 months ago
Filtered Gaussian Processes for Learning with Large Data-Sets
Kernel-based non-parametric models have been applied widely over recent years. However, the associated computational complexity imposes limitations on the applicability of those me...
Jian Qing Shi, Roderick Murray-Smith, D. M. Titter...