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» An Entropic Estimator for Structure Discovery
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NIPS
1998
13 years 10 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 9 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 10 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 11 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 9 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