We study graph estimation and density estimation in high dimensions, using a family of density estimators based on forest structured undirected graphical models. For density estim...
Anupam Gupta, John D. Lafferty, Han Liu, Larry A. ...
—Stochastic relaxation aims at finding the minimum of a fitness function by identifying a proper sequence of distributions, in a given model, that minimize the expected value o...
We propose a system for adaptive streaming from multiple servers to a single receiver over separate network paths. Based on incoming packets, the receiver estimates the available ...
Abstract—In two recent contributions [1], [2], we have provided a comparative analysis of various optimization algorithms, which can be used for atomic location estimation, and s...
Stefano Tennina, Marco Di Renzo, Fabio Graziosi, F...
We develop a methodology for evaluating a decision strategy generated by a stochastic optimization model. The methodology is based on a pilot study in which we estimate the distri...
Robert Rush, John M. Mulvey, John E. Mitchell, Tho...