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JETAI
1998
110views more  JETAI 1998»
13 years 7 months ago
Independency relationships and learning algorithms for singly connected networks
Graphical structures such as Bayesian networks or Markov networks are very useful tools for representing irrelevance or independency relationships, and they may be used to e cientl...
Luis M. de Campos
ADHOC
2010
138views more  ADHOC 2010»
13 years 8 months ago
On the feasibility of UMTS-based Traffic Information Systems
Intelligent Transportation Systems (ITS) are a hot topic in the communications society. Currently, research is primarily focusing on setting up Vehicular Ad Hoc Networks (VANETs) ...
Christoph Sommer, Armin Schmidt, Yi Chen, Reinhard...
ICASSP
2010
IEEE
13 years 8 months ago
Adaptive compressed sensing - A new class of self-organizing coding models for neuroscience
Sparse coding networks, which utilize unsupervised learning to maximize coding efficiency, have successfully reproduced response properties found in primary visual cortex [1]. Ho...
William K. Coulter, Cristopher J. Hillar, Guy Isle...
JMLR
2012
11 years 10 months ago
Deep Boltzmann Machines as Feed-Forward Hierarchies
The deep Boltzmann machine is a powerful model that extracts the hierarchical structure of observed data. While inference is typically slow due to its undirected nature, we argue ...
Grégoire Montavon, Mikio L. Braun, Klaus-Ro...
SASN
2003
ACM
14 years 1 months ago
Modeling vulnerabilities of ad hoc routing protocols
The purpose of this work is to automate the analysis of ad hoc routing protocols in the presence of attackers. To this end, a formal model of protocol behavior is developed in whi...
Shahan Yang, John S. Baras