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ICASSP
2011
IEEE
14 years 3 months ago
Bayesian Compressive Sensing for clustered sparse signals
In traditional framework of Compressive Sensing (CS), only sparse prior on the property of signals in time or frequency domain is adopted to guarantee the exact inverse recovery. ...
Lei Yu, Hong Sun, Jean-Pierre Barbot, Gang Zheng
BMCBI
2010
165views more  BMCBI 2010»
14 years 11 months ago
Bayesian integrated modeling of expression data: a case study on RhoG
Background: DNA microarrays provide an efficient method for measuring activity of genes in parallel and even covering all the known transcripts of an organism on a single array. T...
Rashi Gupta, Dario Greco, Petri Auvinen, Elja Arja...
UM
2005
Springer
15 years 5 months ago
A Bayesian Approach to Modelling Users' Information Display Preferences
This paper describes the process by which we constructed a user model for ERST - an External Representation Selection Tutor - which recommends external representations (ERs) for pa...
Beate Grawemeyer, Richard Cox
SBIA
2010
Springer
14 years 10 months ago
High-Level Modeling of Component-Based CSPs
Most of modern constraint modeling languages combine rich constraint languages with mathematical notations to tackle combinatorial optimization problems. Our purpose is to introduc...
Raphaël Chenouard, Laurent Granvilliers, Rica...
IJON
2010
189views more  IJON 2010»
14 years 10 months ago
Inference and parameter estimation on hierarchical belief networks for image segmentation
We introduce a new causal hierarchical belief network for image segmentation. Contrary to classical tree structured (or pyramidal) models, the factor graph of the network contains...
Christian Wolf, Gérald Gavin