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AAAI
2010
13 years 9 months ago
Efficient Lifting for Online Probabilistic Inference
Lifting can greatly reduce the cost of inference on firstorder probabilistic graphical models, but constructing the lifted network can itself be quite costly. In online applicatio...
Aniruddh Nath, Pedro Domingos
AI
2008
Springer
13 years 6 months ago
MEBN: A language for first-order Bayesian knowledge bases
Although classical first-order logic is the de facto standard logical foundation for artificial intelligence, the lack of a built-in, semantically grounded capability for reasonin...
Kathryn B. Laskey
ICML
2005
IEEE
14 years 9 months ago
Learning first-order probabilistic models with combining rules
Many real-world domains exhibit rich relational structure and stochasticity and motivate the development of models that combine predicate logic with probabilities. These models de...
Sriraam Natarajan, Prasad Tadepalli, Eric Altendor...
BMCBI
2004
126views more  BMCBI 2004»
13 years 8 months ago
A probabilistic model for the evolution of RNA structure
Background: For the purposes of finding and aligning noncoding RNA gene- and cis-regulatory elements in multiple-genome datasets, it is useful to be able to derive multi-sequence ...
Ian Holmes
CLIMA
2006
13 years 9 months ago
Adding Evolving Abilities to a Multi-Agent System
This paper reports on a fertile marriage between madAgents, a Java and Prolog based multi-agent platform, and EVOLP, a logic programming based language to represent and reason abou...
João Leite, Luís Soares