We present in this article a new approximation algorithm for scheduling a set of n independent rigid (meaning requiring a fixed number of processors) jobs on hierarchical parallel ...
In this paper, we investigate the use of parallelization in reinforcement learning (RL), with the goal of learning optimal policies for single-agent RL problems more quickly by us...
Optimization problems with a nuclear norm regularization, such as e.g. low norm matrix factorizations, have seen many applications recently. We propose a new approximation algorit...
In this paper we describe a general grouping technique to devise faster and simpler approximation schemes for several scheduling problems. We illustrate the technique on two diff...
Aleksei V. Fishkin, Klaus Jansen, Monaldo Mastroli...
We give a polynomial approximation scheme for the problem of scheduling on uniformly related parallel machines for a large class of objective functions that depend only on the mac...