In many real-life optimisation problems, there are multiple interacting components in a solution. For example, different components might specify assignments to different kinds of...
Edmund K. Burke, Jakub Marecek, Andrew J. Parkes, ...
We show how a preselection of hidden variables can be used to efficiently train generative models with binary hidden variables. The approach is based on Expectation Maximization (...
We propose a novel boosting algorithm which improves on current algorithms for weighted voting classification by striking a better balance between classification accuracy and the ...
Abstract. Despite the efficiency shown by interior-point methods in large-scale linear programming, they usually perform poorly when applied to multicommodity flow problems. The ne...
We study a wide range of online covering and packing optimization problems. In an online covering problem a linear cost function is known in advance, but the linear constraints th...