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PVLDB
2010
134views more  PVLDB 2010»
14 years 9 months ago
Conditioning and Aggregating Uncertain Data Streams: Going Beyond Expectations
Uncertain data streams are increasingly common in real-world deployments and monitoring applications require the evaluation of complex queries on such streams. In this paper, we c...
Thanh T. L. Tran, Andrew McGregor, Yanlei Diao, Li...
SDM
2011
SIAM
233views Data Mining» more  SDM 2011»
14 years 2 months ago
Multi-Instance Mixture Models
Multi-instance (MI) learning is a variant of supervised learning where labeled examples consist of bags (i.e. multi-sets) of feature vectors instead of just a single feature vecto...
James R. Foulds, Padhraic Smyth
JCPHY
2011
104views more  JCPHY 2011»
14 years 2 months ago
Gaussian beam decomposition of high frequency wave fields using expectation-maximization
A new numerical method for approximating highly oscillatory wave fields as a superposition of Gaussian beams is presented. The method estimates the number of beams and their para...
Gil Ariel, Björn Engquist, Nicolay M. Tanushe...
ISIPTA
2003
IEEE
110views Mathematics» more  ISIPTA 2003»
15 years 4 months ago
Extensions of Expected Utility Theory and Some Limitations of Pairwise Comparisons
We contrast three decision rules that extend Expected Utility to contexts where a convex set of probabilities is used to depict uncertainty: Γ-Maximin, Maximality, and E-admissib...
Mark J. Schervish, Teddy Seidenfeld, Joseph B. Kad...
ICIP
2003
IEEE
16 years 25 days ago
A variational method for Bayesian blind image deconvolution
In this paper the blind image deconvolution (BID) problem is solved using the Bayesian framework. In order to find the parameters of the proposed Bayesian model we present a new g...
Aristidis Likas, Nikolas P. Galatsanos