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ICML
2010
IEEE
15 years 5 months ago
Bottom-Up Learning of Markov Network Structure
The structure of a Markov network is typically learned using top-down search. At each step, the search specializes a feature by conjoining it to the variable or feature that most ...
Jesse Davis, Pedro Domingos
CORR
2011
Springer
168views Education» more  CORR 2011»
14 years 7 months ago
Robustness and modular structure in networks
Many complex systems, from power grids and the internet, to the brain and society, can be modeled using modular networks. Modules, densely interconnected groups of elements, often...
James P. Bagrow, Sune Lehmann, Yong-Yeol Ahn
SP
2006
IEEE
15 years 10 months ago
Deterring Voluntary Trace Disclosure in Re-encryption Mix Networks
An all too real threat to the privacy offered by a mix network is that individual mix administrators may volunteer partial tracing information to a coercer. While this threat can ...
Philippe Golle, XiaoFeng Wang, Markus Jakobsson, A...
IWANN
2009
Springer
15 years 10 months ago
Development of Neural Network Structure with Biological Mechanisms
We present an evolving neural network model in which synapses appear and disappear stochastically according to bio-inspired probabilities. These are in general nonlinear functions ...
Samuel Johnson, Joaquín Marro, Jorge F. Mej...
SECON
2008
IEEE
15 years 10 months ago
Practical Algorithms for Gathering Stored Correlated Data in a Network
—Many sensing systems remotely monitor/measure an environment at several sites, and then report these observations to a central site. We propose and investigate several practical...
Ramin Khalili, James F. Kurose