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ICML
2009
IEEE
16 years 4 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
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ICML
2007
IEEE
16 years 4 months ago
On one method of non-diagonal regularization in sparse Bayesian learning
In the paper we propose a new type of regularization procedure for training sparse Bayesian methods for classification. Transforming Hessian matrix of log-likelihood function to d...
Dmitry Kropotov, Dmitry Vetrov
ICML
2008
IEEE
16 years 4 months ago
Confidence-weighted linear classification
We introduce confidence-weighted linear classifiers, which add parameter confidence information to linear classifiers. Online learners in this setting update both classifier param...
Mark Dredze, Koby Crammer, Fernando Pereira
ICML
2006
IEEE
16 years 4 months ago
Robust probabilistic projections
Principal components and canonical correlations are at the root of many exploratory data mining techniques and provide standard pre-processing tools in machine learning. Lately, p...
Cédric Archambeau, Michel Verleysen, Nicola...
ICML
2006
IEEE
16 years 4 months ago
Pareto optimal linear classification
We consider the problem of choosing a linear classifier that minimizes misclassification probabilities in two-class classification, which is a bi-criterion problem, involving a tr...
Seung-Jean Kim, Alessandro Magnani, Sikandar Samar...