Learning with hidden variables is a central challenge in probabilistic graphical models that has important implications for many real-life problems. The classical approach is usin...
We consider a dense n-user Gaussian interference network formed by paired transmitters and receivers placed independently at random in Euclidean space. Under natural conditions on ...
Matthew Aldridge, Oliver Johnson, Robert J. Piecho...
Using information from failures to guide subsequent search is an important technique for solving combinatorial problems in domains such as boolean satisfiability (SAT) and constr...
— The purpose of this paper is to model the stochastic behavior of nodal prices and use the predicted price differences between zones as the basis for measuring the magnitude and...