: This is a position paper introducing blob computing: A Blob is a generic primitive used to structure a uniform computing substrate into an easier-to-program parallel virtual mach...
In this paper we present an experimental study conducted in 802.11based mesh networks of three existing rate adaptation algorithms. The aim of this study is twofold. On the one ha...
In this paper we present the Dynamic Grow-Shrink Inference-based Markov network learning algorithm (abbreviated DGSIMN), which improves on GSIMN, the state-ofthe-art algorithm for...
Automatic relevance determination (ARD) and the closely-related sparse Bayesian learning (SBL) framework are effective tools for pruning large numbers of irrelevant features leadi...
We study the problem of scheduling permanent jobs on unrelated machines when the objective is to minimize the Lp norm of the machine loads. The problem is known as load balancing ...