It has been discussed in the literature that the mobility of a mobile sensor network (MSN) can be used to improve its sensing coverage. How the mobility can efficiently be managed ...
There has been a recent, growing interest in classification and link prediction in structured domains. Methods such as conditional random fields and relational Markov networks sup...
Markov networks are a common class of graphical models used in machine learning. Such models use an undirected graph to capture dependency information among random variables in a ...
Bayesian networks provide a modeling language and associated inference algorithm for stochastic domains. They have been successfully applied in a variety of medium-scale applicati...
Neural gas (NG) constitutes a very robust clustering algorithm which can be derived as stochastic gradient descent from a cost function closely connected to the quantization error...
Barbara Hammer, Alexander Hasenfuss, Thomas Villma...