Abstract. The aim of this paper is to present and analyze a class of hpversion discontinuous Galerkin (DG) discretizations for the numerical approximation of linear elliptic proble...
Using a general polynomial approximation approach, we present an arithmetic library generator for the logarithmic number system (LNS). The generator produces optimized LNS arithmet...
This paper proposes a new randomized strategy for adaptive MCMC using Bayesian optimization. This approach applies to nondifferentiable objective functions and trades off explor...
We present an algorithm that learns invariant features from real data in an entirely unsupervised fashion. The principal benefit of our method is that it can be applied without hu...
In this paper, we investigate multi-agent learning (MAL) in a multi-agent resource selection problem (MARS) in which a large group of agents are competing for common resources. Si...