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» Learning with Tree-Averaged Densities and Distributions
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TIT
2008
61views more  TIT 2008»
13 years 7 months ago
A Probabilistic Upper Bound on Differential Entropy
A novel, non-trivial, probabilistic upper bound on the entropy of an unknown one-dimensional distribution, given the support of the distribution and a sample from that distribution...
Erik G. Learned-Miller, Joseph DeStefano
ICMLA
2009
13 years 5 months ago
Alive on Back-feed Culprit Identification via Machine Learning
We describe an application of machine learning techniques toward the problem of predicting which network protector switch is the cause of an Alive on Back-Feed (ABF) event in the ...
Bert C. Huang, Ansaf Salleb-Aouissi, Philip Gross
TSMC
2008
128views more  TSMC 2008»
13 years 7 months ago
Adaptive Sensor Placement and Boundary Estimation for Monitoring Mass Objects
Sensor networks are widely used in monitoring and tracking a large number of objects. Without prior knowledge on the dynamics of object distribution, their density estimation could...
Zhen Guo, MengChu Zhou, Guofei Jiang
ICPR
2004
IEEE
14 years 9 months ago
Visual Learning and Recognition of a Probabilistic Spatio-Temporal Model of Cyclic Human Locomotion
We present a novel representation of cyclic human locomotion based on a set of spatio-temporal curves of tracked points on the surface of a person. We start by extracting a set of...
Miha Peternel, Ales Leonardis
ESANN
2003
13 years 9 months ago
Robust Topology Representing Networks
Martinetz and Schulten proposed the use of a Competitive Hebbian Learning (CHL) rule to build Topology Representing Networks. From a set of units and a data distribution, a link i...
Michaël Aupetit