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» Optimal Nonlinear Prediction of Random Fields on Networks
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CORR
2010
Springer
98views Education» more  CORR 2010»
13 years 7 months ago
Linear Operator Channels over Finite Fields
Motivated by random linear network coding, we study the communication through channels, called linear operator channels (LOCs), that perform linear operation over finite fields. Fo...
Shenghao Yang, Siu-Wai Ho, Jin Meng, En-Hui Yang
ICASSP
2009
IEEE
14 years 2 months ago
Field inversion by consensus and compressed sensing
— We study the inversion of a random field from pointwise measurements collected by a sensor network. We assume that the field has a sparse representation in a known basis. To ...
Aurora Schmidt, José M. F. Moura
CORR
2008
Springer
158views Education» more  CORR 2008»
13 years 7 months ago
Distributed and Recursive Parameter Estimation in Parametrized Linear State-Space Models
We consider a network of sensors deployed to sense a spatio-temporal field and infer parameters of interest about the field. We are interested in the case where each sensor's...
S. Sundhar Ram, Venugopal V. Veeravalli, Angelia N...
CORR
2008
Springer
150views Education» more  CORR 2008»
13 years 7 months ago
A Local Mean Field Analysis of Security Investments in Networks
Getting agents in the Internet, and in networks in general, to invest in and deploy security features and protocols is a challenge, in particular because of economic reasons arisi...
Marc Lelarge, Jean Bolot
CVPR
2007
IEEE
14 years 9 months ago
Discriminative Learning of Dynamical Systems for Motion Tracking
We introduce novel discriminative learning algorithms for dynamical systems. Models such as Conditional Random Fields or Maximum Entropy Markov Models outperform the generative Hi...
Minyoung Kim, Vladimir Pavlovic