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» Optimal Sequential Exploration: A Binary Learning Model
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ICML
2009
IEEE
14 years 9 months ago
Convex variational Bayesian inference for large scale generalized linear models
We show how variational Bayesian inference can be implemented for very large generalized linear models. Our relaxation is proven to be a convex problem for any log-concave model. ...
Hannes Nickisch, Matthias W. Seeger
ICA
2010
Springer
13 years 9 months ago
Binary Sparse Coding
We study a sparse coding learning algorithm that allows for a simultaneous learning of the data sparseness and the basis functions. The algorithm is derived based on a generative m...
Marc Henniges, Gervasio Puertas, Jörg Bornsch...
ICML
2005
IEEE
14 years 9 months ago
Optimizing abstaining classifiers using ROC analysis
Classifiers that refrain from classification in certain cases can significantly reduce the misclassification cost. However, the parameters for such abstaining classifiers are ofte...
Tadeusz Pietraszek
PAMI
2002
112views more  PAMI 2002»
13 years 8 months ago
Recognizing Handwritten Digits Using Hierarchical Products of Experts
The product of experts learning procedure [1] can discover a set of stochastic binary features that constitute a nonlinear generative model of handwritten images of digits. The qua...
Guy Mayraz, Geoffrey E. Hinton
GECCO
2003
Springer
124views Optimization» more  GECCO 2003»
14 years 1 months ago
Using an Immune System Model to Explore Mate Selection in Genetic Algorithms
Abstract. When Genetic Algorithms (GAs) are employed in multimodal function optimization, engineering and machine learning, identifying multiple peaks and maintaining subpopulation...
Chien-Feng Huang