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» The Inference Problem: A Survey
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ICONIP
2009
15 years 5 months ago
Learning Gaussian Process Models from Uncertain Data
It is generally assumed in the traditional formulation of supervised learning that only the outputs data are uncertain. However, this assumption might be too strong for some learni...
Patrick Dallaire, Camille Besse, Brahim Chaib-draa
ICASSP
2011
IEEE
14 years 11 months ago
Optimized edge appearance probability for cooperative localization based on tree-reweighted nonparametric belief propagation
Nonparametric belief propagation (NBP) is a well-known particlebased method for distributed inference in wireless networks. NBP has a large number of applications, including coope...
Vladimir Savic, Henk Wymeersch, Federico Penna, Sa...
CORR
2012
Springer
196views Education» more  CORR 2012»
14 years 3 months ago
PAC-Bayesian Policy Evaluation for Reinforcement Learning
Bayesian priors offer a compact yet general means of incorporating domain knowledge into many learning tasks. The correctness of the Bayesian analysis and inference, however, lar...
Mahdi Milani Fard, Joelle Pineau, Csaba Szepesv&aa...
CVPR
2000
IEEE
16 years 9 months ago
Integrating Color, Texture, and Geometry for Image Retrieval
This paper examines the problem of image retrieval from large, heterogeneous image databases. We present a technique that fulfills several needs identified by surveying recent res...
Nicholas R. Howe, Daniel P. Huttenlocher
ICDE
2009
IEEE
202views Database» more  ICDE 2009»
16 years 9 months ago
Tracking High Quality Clusters over Uncertain Data Streams
Recently, data mining over uncertain data streams has attracted a lot of attentions because of the widely existed imprecise data generated from a variety of streaming applications....
Chen Zhang, Ming Gao, Aoying Zhou