We give new algorithms for a variety of randomly-generated instances of computational problems using a linearization technique that reduces to solving a system of linear equations...
One of the central challenges in reinforcement learning is to balance the exploration/exploitation tradeoff while scaling up to large problems. Although model-based reinforcement ...
A vital task facing government agencies and commercial organizations that report data is to represent the data in a meaningful way and simultaneously to protect the confidentialit...
Fred Glover, Lawrence H. Cox, Rahul Patil, James P...
—We develop an algorithm aimed at estimating travel time on segments of a road network using a convex optimization framework. Sampled travel time from probe vehicles are assumed ...
Sebastien Blandin, Laurent El Ghaoui, Alexandre M....
Abstract. This paper deals with the problem of nurse rostering in Belgian hospitals. This is a highly constrained real world problem that was (until the results of this research we...
Edmund K. Burke, Patrick De Causmaecker, Greet Van...