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IJCAI
2001
13 years 9 months ago
Approximate inference for first-order probabilistic languages
A new, general approach is described for approximate inference in first-order probabilistic languages, using Markov chain Monte Carlo (MCMC) techniques in the space of concrete po...
Hanna Pasula, Stuart J. Russell
IMC
2006
ACM
14 years 1 months ago
A multifaceted approach to understanding the botnet phenomenon
The academic community has long acknowledged the existence of malicious botnets, however to date, very little is known about the behavior of these distributed computing platforms....
Moheeb Abu Rajab, Jay Zarfoss, Fabian Monrose, And...
SIGMOD
2008
ACM
169views Database» more  SIGMOD 2008»
14 years 8 months ago
MCDB: a monte carlo approach to managing uncertain data
To deal with data uncertainty, existing probabilistic database systems augment tuples with attribute-level or tuple-level probability values, which are loaded into the database al...
Ravi Jampani, Fei Xu, Mingxi Wu, Luis Leopoldo Per...
CVPR
2004
IEEE
13 years 11 months ago
Learning in Region-Based Image Retrieval with Generalized Support Vector Machines
Relevance feedback approaches based on support vector machine (SVM) learning have been applied to significantly improve retrieval performance in content-based image retrieval (CBI...
Iker Gondra, Douglas R. Heisterkamp
BMCBI
2010
72views more  BMCBI 2010»
13 years 8 months ago
Phylogenetic representativeness: a new method for evaluating taxon sampling in evolutionary studies
Background: Taxon sampling is a major concern in phylogenetic studies. Incomplete, biased, or improper taxon sampling can lead to misleading results in reconstructing evolutionary...
Federico Plazzi, Ronald R. Ferrucci, Marco Passamo...