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HIS
2003
13 years 9 months ago
A Hybrid Approach for Learning Parameters of Probabilistic Networks from Incomplete Databases
– Probabilistic Inference Networks are becoming increasingly popular for modeling and reasoning in uncertain domains. In the past few years, many efforts have been made in learni...
S. Haider
IJCNN
2008
IEEE
14 years 2 months ago
On the learning of nonlinear visual features from natural images by optimizing response energies
— The operation of V1 simple cells in primates has been traditionally modelled with linear models resembling Gabor filters, whereas the functionality of subsequent visual cortic...
Jussi T. Lindgren, Aapo Hyvärinen
CIKM
2009
Springer
14 years 2 months ago
Learning to rank from Bayesian decision inference
Ranking is a key problem in many information retrieval (IR) applications, such as document retrieval and collaborative filtering. In this paper, we address the issue of learning ...
Jen-Wei Kuo, Pu-Jen Cheng, Hsin-Min Wang
CVPR
2008
IEEE
14 years 2 months ago
Learning a geometry integrated image appearance manifold from a small training set
While low-dimensional image representations have been very popular in computer vision, they suffer from two limitations: (i) they require collecting a large and varied training se...
Yilei Xu, Amit K. Roy Chowdhury
COLT
2005
Springer
14 years 1 months ago
Separating Models of Learning from Correlated and Uncorrelated Data
We consider a natural framework of learning from correlated data, in which successive examples used for learning are generated according to a random walk over the space of possibl...
Ariel Elbaz, Homin K. Lee, Rocco A. Servedio, Andr...