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» Multi-sensor Data Fusion Using the Influence Model
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CSDA
2006
94views more  CSDA 2006»
13 years 8 months ago
The nature of sensitivity in monotone missing not at random models
Models for incomplete longitudinal data under missingness not at random have gained some popularity. At the same time, cautionary remarks have been issued regarding their sensitiv...
Ivy Jansen, Niel Hens, Geert Molenberghs, Marc Aer...
ICML
2005
IEEE
14 years 9 months ago
Learning first-order probabilistic models with combining rules
Many real-world domains exhibit rich relational structure and stochasticity and motivate the development of models that combine predicate logic with probabilities. These models de...
Sriraam Natarajan, Prasad Tadepalli, Eric Altendor...
AVSS
2007
IEEE
14 years 3 months ago
Model-based human posture estimation for gesture analysis in an opportunistic fusion smart camera network
In multi-camera networks rich visual data is provided both spatially and temporally. In this paper a method of human posture estimation is described incorporating the concept of a...
Chen Wu, Hamid K. Aghajan
BMCBI
2008
107views more  BMCBI 2008»
13 years 8 months ago
A machine learning approach to explore the spectra intensity pattern of peptides using tandem mass spectrometry data
Background: A better understanding of the mechanisms involved in gas-phase fragmentation of peptides is essential for the development of more reliable algorithms for high-throughp...
Cong Zhou, Lucas D. Bowler, Jianfeng Feng
KDD
2012
ACM
238views Data Mining» more  KDD 2012»
11 years 11 months ago
Multi-source learning for joint analysis of incomplete multi-modality neuroimaging data
Incomplete data present serious problems when integrating largescale brain imaging data sets from different imaging modalities. In the Alzheimer’s Disease Neuroimaging Initiativ...
Lei Yuan, Yalin Wang, Paul M. Thompson, Vaibhav A....