Abstract. Real-world optimization problems are often subject to uncertainties, which can arise regarding stochastic model parameters, objective functions and decision variables. Th...
Distributed optimal traffic engineering in the presence of multiple paths has been found to be a difficult problem to solve. In this paper, we introduce a new approach in an attem...
Searching the space of policies directly for the optimal policy has been one popular method for solving partially observable reinforcement learning problems. Typically, with each ...
Recent work has provided functions that can be used to prove a principled distinction between the capabilities of mutation-based and crossover-based algorithms. However, prior fun...
We study the cosegmentation problem where the objective
is to segment the same object (i.e., region) from a pair
of images. The segmentation for each image can be cast
using a p...