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CVPR
2008
IEEE
14 years 9 months ago
Learning Bayesian Networks with qualitative constraints
Graphical models such as Bayesian Networks (BNs) are being increasingly applied to various computer vision problems. One bottleneck in using BN is that learning the BN model param...
Yan Tong, Qiang Ji
TWC
2010
13 years 2 months ago
Distributed consensus-based demodulation: algorithms and error analysis
This paper deals with distributed demodulation of space-time transmissions of a common message from a multiantenna access point (AP) to a wireless sensor network. Based on local me...
Hao Zhu, Alfonso Cano, Georgios B. Giannakis
TNN
1998
114views more  TNN 1998»
13 years 7 months ago
Bayesian retrieval in associative memories with storage errors
Abstract—It is well known that for finite-sized networks, onestep retrieval in the autoassociative Willshaw net is a suboptimal way to extract the information stored in the syna...
Friedrich T. Sommer, Peter Dayan
CORR
2012
Springer
170views Education» more  CORR 2012»
12 years 3 months ago
What Cannot be Learned with Bethe Approximations
We address the problem of learning the parameters in graphical models when inference is intractable. A common strategy in this case is to replace the partition function with its B...
Uri Heinemann, Amir Globerson
ICRA
2005
IEEE
131views Robotics» more  ICRA 2005»
14 years 1 months ago
Model-based Shape Analysis of Gas Concentration Gridmaps for Improved Gas Source Localisation
Abstract— This work addresses the capability to use concentration gridmaps to locate a static gas source. In previous works it was found that depending on the shape of the mapped...
Achim J. Lilienthal, Felix Streichert, Andreas Zel...