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PKDD
2009
Springer
184views Data Mining» more  PKDD 2009»
15 years 4 months ago
Learning Preferences with Hidden Common Cause Relations
Abstract. Gaussian processes have successfully been used to learn preferences among entities as they provide nonparametric Bayesian approaches for model selection and probabilistic...
Kristian Kersting, Zhao Xu
83
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WWW
2006
ACM
15 years 10 months ago
Probabilistic models for discovering e-communities
The increasing amount of communication between individuals in e-formats (e.g. email, Instant messaging and the Web) has motivated computational research in social network analysis...
Ding Zhou, Eren Manavoglu, Jia Li, C. Lee Giles, H...
71
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BMCBI
2007
125views more  BMCBI 2007»
14 years 9 months ago
Bayesian meta-analysis models for microarray data: a comparative study
Background: With the growing abundance of microarray data, statistical methods are increasingly needed to integrate results across studies. Two common approaches for meta-analysis...
Erin M. Conlon, Joon J. Song, Anna Liu
NIPS
2001
14 years 11 months ago
Probabilistic Inference of Hand Motion from Neural Activity in Motor Cortex
Statistical learning and probabilistic inference techniques are used to infer the hand position of a subject from multi-electrode recordings of neural activity in motor cortex. Fi...
Yun Gao, Michael J. Black, Elie Bienenstock, Shy S...
AROBOTS
2011
14 years 4 months ago
Learning GP-BayesFilters via Gaussian process latent variable models
Abstract— GP-BayesFilters are a general framework for integrating Gaussian process prediction and observation models into Bayesian filtering techniques, including particle filt...
Jonathan Ko, Dieter Fox