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JMLR
2011
125views more  JMLR 2011»
13 years 2 months ago
Approximate Marginals in Latent Gaussian Models
We consider the problem of improving the Gaussian approximate posterior marginals computed by expectation propagation and the Laplace method in latent Gaussian models and propose ...
Botond Cseke, Tom Heskes
JMLR
2010
144views more  JMLR 2010»
13 years 2 months ago
Maximum Margin Learning with Incomplete Data: Learning Networks instead of Tables
In this paper we address the problem of predicting when the available data is incomplete. We show that changing the generally accepted table-wise view of the sample items into a g...
Sándor Szedmák, Yizhao Ni, Steve R. ...
KDD
2009
ACM
175views Data Mining» more  KDD 2009»
13 years 12 months ago
Multi-class protein fold recognition using large margin logic based divide and conquer learning
Inductive Logic Programming (ILP) systems have been successfully applied to solve complex problems in bioinformatics by viewing them as binary classification tasks. It remains an...
Huma Lodhi, Stephen Muggleton, Michael J. E. Stern...
COLT
2000
Springer
13 years 11 months ago
PAC Analogues of Perceptron and Winnow via Boosting the Margin
We describe a novel family of PAC model algorithms for learning linear threshold functions. The new algorithms work by boosting a simple weak learner and exhibit complexity bounds...
Rocco A. Servedio
ICML
2010
IEEE
13 years 8 months ago
Large Scale Max-Margin Multi-Label Classification with Priors
We propose a max-margin formulation for the multi-label classification problem where the goal is to tag a data point with a set of pre-specified labels. Given a set of L labels, a...
Bharath Hariharan, Lihi Zelnik-Manor, S. V. N. Vis...