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SAC
2008
ACM
14 years 9 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....
NAACL
2010
14 years 8 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 ...
ACL
2009
14 years 8 months 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 5 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 12 days 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