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118
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SAC
2008
ACM
15 years 1 months ago
Bayesian inference for a discretely observed stochastic kinetic model
The ability to infer parameters of gene regulatory networks is emerging as a key problem in systems biology. The biochemical data are intrinsically stochastic and tend to be observ...
Richard J. Boys, Darren J. Wilkinson, Thomas B. L....
114
Voted
NAACL
2010
15 years 4 days 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 ...
ACL
2009
15 years 2 days ago
Compiling a Massive, Multilingual Dictionary via Probabilistic Inference
Can we automatically compose a large set of Wiktionaries and translation dictionaries to yield a massive, multilingual dictionary whose coverage is substantially greater than that...
Mausam, Stephen Soderland, Oren Etzioni, Daniel S....
PADL
2012
Springer
13 years 9 months ago
LearnPADS + + : Incremental Inference of Ad Hoc Data Formats
An ad hoc data source is any semi-structured, non-standard data source. The format of such data sources is often evolving and frequently lacking documentation. Consequently, off-t...
Kenny Qili Zhu, Kathleen Fisher, David Walker
AAAI
2008
15 years 4 months ago
Lifted First-Order Belief Propagation
Unifying first-order logic and probability is a long-standing goal of AI, and in recent years many representations combining aspects of the two have been proposed. However, infere...
Parag Singla, Pedro Domingos