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UAI
2003
15 years 6 months ago
Large-Sample Learning of Bayesian Networks is NP-Hard
In this paper, we provide new complexity results for algorithms that learn discrete-variable Bayesian networks from data. Our results apply whenever the learning algorithm uses a ...
David Maxwell Chickering, Christopher Meek, David ...
UAI
2003
15 years 6 months ago
Learning Continuous Time Bayesian Networks
Continuous time Bayesian networks (CTBN) describe structured stochastic processes with finitely many states that evolve over continuous time. A CTBN is a directed (possibly cycli...
Uri Nodelman, Christian R. Shelton, Daphne Koller
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UAI
2003
15 years 6 months ago
Strong Faithfulness and Uniform Consistency in Causal Inference
A fundamental question in causal inference is whether it is possible to reliably infer the manipulation effects from observational data. There are a variety of senses of asymptot...
Jiji Zhang, Peter Spirtes
COLING
2000
15 years 6 months ago
Word Sense Disambiguation of Adjectives Using Probabilistic Networks
In this paper, word sense dismnbiguation (WSD) accuracy achievable by a probabilistic classifier, using very milfimal training sets, is investigated. \Ve made the assuml)tiou that...
Gerald Chao, Michael G. Dyer
CCCG
1998
15 years 6 months ago
A modified longest side bisection triangulation
Fast and efficient exploration of large terrains in a virtual reality manner requires different levels of detail to speedup processing of terrain parts in background. Thus, the tr...
Christoph Stamm, Stephan Eidenbenz, Renato Pajarol...
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