Practical Recurrent Learning (PRL) has been proposed as a simple learning algorithm for recurrent neural networks[1][2]. This algorithm enables learning with practical order O(n2 )...
Linear Programming (LP) relaxations have become powerful tools for finding the most probable (MAP) configuration in graphical models. These relaxations can be solved efficiently u...
David Sontag, Talya Meltzer, Amir Globerson, Tommi...
Gaussian process classifiers (GPCs) are Bayesian probabilistic kernel classifiers. In GPCs, the probability of belonging to a certain class at an input location is monotonically re...
This paper studies a virus inoculation game on social networks. A framework is presented which allows the measuring of the windfall of friendship, i.e., how much players benefit i...
Dominic Meier, Yvonne Anne Oswald, Stefan Schmid, ...
Underwater acoustic localization usually relies on time of arrival (ToA) measurements, which are then converted into range estimates. However, the water medium is inhomogeneous and...
Christian R. Berger, Shengli Zhou, Peter Willett, ...