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PRICAI
2004
Springer
14 years 3 months ago
An Anytime Algorithm for Interpreting Arguments
Abstract. The problem of interpreting Natural Language (NL) discourse is generally of exponential complexity. However, since interactions with users must be conducted in real time,...
Sarah George, Ingrid Zukerman, Michael Niemann
ECML
2006
Springer
14 years 1 months ago
EM Algorithm for Symmetric Causal Independence Models
Causal independence modelling is a well-known method both for reducing the size of probability tables and for explaining the underlying mechanisms in Bayesian networks. In this pap...
Rasa Jurgelenaite, Tom Heskes
UAI
1994
13 years 11 months ago
Approximation Algorithms for the Loop Cutset Problem
We show how to nd a minimum weight loop cutset in a Bayesian network with high probability. Finding such a loop cutset is the rst step in the method of conditioning for inference....
Ann Becker, Dan Geiger
ICASSP
2010
IEEE
13 years 10 months ago
Algorithms for robust linear regression by exploiting the connection to sparse signal recovery
In this paper, we develop algorithms for robust linear regression by leveraging the connection between the problems of robust regression and sparse signal recovery. We explicitly ...
Yuzhe Jin, Bhaskar D. Rao
CORR
2007
Springer
169views Education» more  CORR 2007»
13 years 10 months ago
Algorithmic Complexity Bounds on Future Prediction Errors
We bound the future loss when predicting any (computably) stochastic sequence online. Solomonoff finitely bounded the total deviation of his universal predictor M from the true d...
Alexey V. Chernov, Marcus Hutter, Jürgen Schm...