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» An Entropic Estimator for Structure Discovery
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NIPS
1998
13 years 6 months ago
An Entropic Estimator for Structure Discovery
We introduce a novel framework for simultaneous structure and parameter learning in hidden-variable conditional probability models, based on an entropic prior and a solution for i...
Matthew Brand
CAS
2008
118views more  CAS 2008»
13 years 5 months ago
A Novel Method for Measuring the Structural Information Content of Networks
In this paper we first present a novel approach to determine the structural information content (graph entropy) of a network represented by an undirected and connected graph. Such...
Matthias Dehmer
UAI
2000
13 years 6 months ago
Utilities as Random Variables: Density Estimation and Structure Discovery
Decision theory does not traditionally include uncertainty over utility functions. We argue that the a person's utility value for a given outcome can be treated as we treat o...
Urszula Chajewska, Daphne Koller
DCOSS
2008
Springer
13 years 6 months ago
An Information Theoretic Framework for Field Monitoring Using Autonomously Mobile Sensors
We consider a mobile sensor network monitoring a spatio-temporal field. Given limited caches at the sensor nodes, the goal is to develop a distributed cache management algorithm to...
Hany Morcos, George Atia, Azer Bestavros, Ibrahim ...
BMCBI
2007
120views more  BMCBI 2007»
13 years 5 months ago
Re-sampling strategy to improve the estimation of number of null hypotheses in FDR control under strong correlation structures
Background: When conducting multiple hypothesis tests, it is important to control the number of false positives, or the False Discovery Rate (FDR). However, there is a tradeoff be...
Xin Lu, David L. Perkins