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» Multi-sensor Data Fusion Using the Influence Model
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ICML
2005
IEEE
14 years 9 months ago
A model for handling approximate, noisy or incomplete labeling in text classification
We introduce a Bayesian model, BayesANIL, that is capable of estimating uncertainties associated with the labeling process. Given a labeled or partially labeled training corpus of...
Ganesh Ramakrishnan, Krishna Prasad Chitrapura, Ra...
BMCBI
2005
97views more  BMCBI 2005»
13 years 8 months ago
Modelling the correlation between the activities of adjacent genes in drosophila
Background: Correlation between the expression levels of genes which are located close to each other on the genome has been found in various organisms, including yeast, drosophila...
Helene H. Thygesen, Aeilko H. Zwinderman
TIT
2008
141views more  TIT 2008»
13 years 8 months ago
Dimensionality Reduction for Distributed Estimation in the Infinite Dimensional Regime
Distributed estimation of an unknown signal is a common task in sensor networks. The scenario usually envisioned consists of several nodes, each making an observation correlated wi...
Olivier Roy, Martin Vetterli
GECCO
2007
Springer
162views Optimization» more  GECCO 2007»
14 years 2 months ago
Using pair approximations to predict takeover dynamics in spatially structured populations
The topological properties of a network directly impact the flow of information through a system. For example, in natural populations, the network of inter-individual contacts aff...
Joshua L. Payne, Margaret J. Eppstein
AMFG
2005
IEEE
203views Biometrics» more  AMFG 2005»
14 years 2 months ago
Learning to Fuse 3D+2D Based Face Recognition at Both Feature and Decision Levels
2D intensity images and 3D shape models are both useful for face recognition, but in different ways. While algorithms have long been developed using 2D or 3D data, recently has see...
Stan Z. Li, ChunShui Zhao, Meng Ao, Zhen Lei