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JMLR
2010
134views more  JMLR 2010»
14 years 6 months ago
Bayesian Algorithms for Causal Data Mining
We present two Bayesian algorithms CD-B and CD-H for discovering unconfounded cause and effect relationships from observational data without assuming causal sufficiency which prec...
Subramani Mani, Constantin F. Aliferis, Alexander ...
INFOCOM
2008
IEEE
15 years 6 months ago
Minerva: Learning to Infer Network Path Properties
—Knowledge of the network path properties such as latency, hop count, loss and bandwidth is key to the performance of overlay networks, grids and p2p applications. Network operat...
Rita H. Wouhaybi, Puneet Sharma, Sujata Banerjee, ...
PR
2011
14 years 6 months ago
A variational Bayesian methodology for hidden Markov models utilizing Student's-t mixtures
The Student’s-t hidden Markov model (SHMM) has been recently proposed as a robust to outliers form of conventional continuous density hidden Markov models, trained by means of t...
Sotirios Chatzis, Dimitrios I. Kosmopoulos
CVPR
2009
IEEE
1382views Computer Vision» more  CVPR 2009»
16 years 7 months ago
Super-Resolution via Recapture and Bayesian Effect Modeling
This paper presents Bayesian edge inference (BEI), a single-frame super-resolution method explicitly grounded in Bayesian inference that addresses issues common to existing meth...
Bryan S. Morse, Dan Ventura, Kevin D. Seppi, Neil ...
IICAI
2003
15 years 1 months ago
The Acyclic Bayesian Net Generator
Abstract. We present the Acyclic Bayesian Net Generator, a new approach to learn the structure of a Bayesian network using genetic algorithms. Due to the encoding mechanism, acycli...
Pankaj B. Gupta, Vicki H. Allan