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UAI
2003
13 years 11 months ago
The Information Bottleneck EM Algorithm
Learning with hidden variables is a central challenge in probabilistic graphical models that has important implications for many real-life problems. The classical approach is usin...
Gal Elidan, Nir Friedman
NIPS
2000
13 years 11 months ago
On Reversing Jensen's Inequality
Jensen's inequality is a powerful mathematical tool and one of the workhorses in statistical learning. Its applications therein include the EM algorithm, Bayesian estimation ...
Tony Jebara, Alex Pentland
NIPS
1996
13 years 11 months ago
Early Brain Damage
Optimal Brain Damage (OBD) is a method for reducing the number of weights in a neural network. OBD estimates the increase in cost function if weights are pruned and is a valid app...
Volker Tresp, Ralph Neuneier, Hans-Georg Zimmerman...
ICML
2010
IEEE
13 years 11 months ago
Accelerated dual decomposition for MAP inference
Approximate MAP inference in graphical models is an important and challenging problem for many domains including computer vision, computational biology and natural language unders...
Vladimir Jojic, Stephen Gould, Daphne Koller
ICML
2010
IEEE
13 years 11 months ago
A Simple Algorithm for Nuclear Norm Regularized Problems
Optimization problems with a nuclear norm regularization, such as e.g. low norm matrix factorizations, have seen many applications recently. We propose a new approximation algorit...
Martin Jaggi, Marek Sulovský