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 ...
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...
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...
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 ...
—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...