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UAI
1998
13 years 9 months ago
Large Deviation Methods for Approximate Probabilistic Inference
We study two-layer belief networks of binary random variables in which the conditional probabilities Pr childjparents depend monotonically on weighted sums of the parents. In larg...
Michael J. Kearns, Lawrence K. Saul
NAACL
2010
13 years 6 months ago
Bayesian Inference for Finite-State Transducers
We describe a Bayesian inference algorithm that can be used to train any cascade of weighted finite-state transducers on end-toend data. We also investigate the problem of automat...
David Chiang, Jonathan Graehl, Kevin Knight, Adam ...
PET
2009
Springer
14 years 3 months ago
Vida: How to Use Bayesian Inference to De-anonymize Persistent Communications
We present the Vida family of abstractions of anonymous communication systems, model them probabilistically and apply Bayesian inference to extract patterns of communications and u...
George Danezis, Carmela Troncoso
EACL
2009
ACL Anthology
14 years 9 months ago
Cube Summing, Approximate Inference with Non-Local Features, and Dynamic Programming without Semirings
We introduce cube summing, a technique that permits dynamic programming algorithms for summing over structures (like the forward and inside algorithms) to be extended with non-loc...
Kevin Gimpel, Noah A. Smith
CORR
2010
Springer
143views Education» more  CORR 2010»
13 years 8 months ago
Expressiveness of Generic Process Shape Types
METAI is a generic process calculus that can be instantiated by supplying rewriting rules defining an operational semantics to make numerous process calculi such as the -calculus,...
Jan Jakubuv, J. B. Wells