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UAI
2004
13 years 11 months ago
Graph Partition Strategies for Generalized Mean Field Inference
An autonomous variational inference algorithm for arbitrary graphical models requires the ability to optimize variational approximations over the space of model parameters as well...
Eric P. Xing, Michael I. Jordan
SLP
1989
87views more  SLP 1989»
13 years 11 months ago
Partial Evaluation in Prolog: Some Improvements about Cut
Two main aspects of Partial Evaluation for Prolog programs are considered: treatment of cuts and control of recursion. The analysis about cut is exhaustive: we consider occurrence...
Michele Bugliesi, F. Russo
CORR
2010
Springer
176views Education» more  CORR 2010»
13 years 9 months ago
A General Framework for Graph Sparsification
Given a weighted graph G and an error parameter > 0, the graph sparsification problem requires sampling edges in G and giving the sampled edges appropriate weights to obtain a...
Ramesh Hariharan, Debmalya Panigrahi
ICML
2004
IEEE
14 years 10 months ago
Semi-supervised learning using randomized mincuts
In many application domains there is a large amount of unlabeled data but only a very limited amount of labeled training data. One general approach that has been explored for util...
Avrim Blum, John D. Lafferty, Mugizi Robert Rweban...
SIGDOC
2004
ACM
14 years 3 months ago
Signal to noise ratio of information in documentation
The signal to noise ratio is a common concept in radio communications and electronic communication in general. For a radio, the static is the noise. Too much static and the storm ...
Michael J. Albers