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NIPS
2008
13 years 9 months ago
Posterior Consistency of the Silverman g-prior in Bayesian Model Choice
Kernel supervised learning methods can be unified by utilizing the tools from regularization theory. The duality between regularization and prior leads to interpreting regularizat...
Zhihua Zhang, Michael I. Jordan, Dit-Yan Yeung
VISAPP
2010
13 years 5 months ago
Inverse Problems in Imaging and Computer Vision - From Regularization Theory to Bayesian Inference
phies are also mentioned and a common mathematical abstraction for all these inverses problems will be presented. By focusing on a simple linear forward model, first a synthetic an...
Ali Mohammad-Djafari
TCSV
2008
87views more  TCSV 2008»
13 years 7 months ago
On Iterative Regularization and Its Application
Many existing techniques for image restoration can be expressed in terms of minimizing a particular cost function. Iterative regularization methods are a novel variation on this th...
Michael R. Charest, Peyman Milanfar
ECCV
2008
Springer
14 years 9 months ago
Local Regularization for Multiclass Classification Facing Significant Intraclass Variations
We propose a new local learning scheme that is based on the principle of decisiveness: the learned classifier is expected to exhibit large variability in the direction of the test ...
Lior Wolf, Yoni Donner
ECCV
2008
Springer
14 years 9 months ago
SERBoost: Semi-supervised Boosting with Expectation Regularization
The application of semi-supervised learning algorithms to large scale vision problems suffers from the bad scaling behavior of most methods. Based on the Expectation Regularization...
Amir Saffari, Helmut Grabner, Horst Bischof