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CSE
2009
IEEE
15 years 6 months ago
Inferring the Maximum Likelihood Hierarchy in Social Networks
—Individuals in social networks are often organized under some hierarchy such as a command structure. In many cases, when this structure is unknown, there is a need to discover h...
Arun S. Maiya, Tanya Y. Berger-Wolf
ECCV
2008
Springer
16 years 1 months ago
Constrained Maximum Likelihood Learning of Bayesian Networks for Facial Action Recognition
Probabilistic graphical models such as Bayesian Networks have been increasingly applied to many computer vision problems. Accuracy of inferences in such models depends on the quali...
Cassio Polpo de Campos, Yan Tong, Qiang Ji
94
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SIGMETRICS
2002
ACM
115views Hardware» more  SIGMETRICS 2002»
14 years 11 months ago
Maximum likelihood network topology identification from edge-based unicast measurements
Network tomography is a process for inferring "internal" link-level delay and loss performance information based on end-to-end (edge) network measurements. These methods...
Mark Coates, Rui Castro, Robert Nowak, Manik Gadhi...
TSP
2008
103views more  TSP 2008»
14 years 11 months ago
Distributed Adaptive Quantization for Wireless Sensor Networks: From Delta Modulation to Maximum Likelihood
Abstract-- We consider distributed parameter estimation using quantized observations in wireless sensor networks where due to bandwidth constraint, each sensor quantizes its local ...
Jun Fang, Hongbin Li
TNN
2008
82views more  TNN 2008»
14 years 11 months ago
Deterministic Learning for Maximum-Likelihood Estimation Through Neural Networks
In this paper, a general method for the numerical solution of maximum-likelihood estimation (MLE) problems is presented; it adopts the deterministic learning (DL) approach to find ...
Cristiano Cervellera, Danilo Macciò, Marco ...