This paper is concerned with personalisation of user agents by symbolic, on-line machine learning techniques. The application of these ideas to an infotainment agent is discussed ...
Joshua J. Cole, Matt J. Gray, John W. Lloyd, Kee S...
Many irregular scientific computing problems can be modeled by directed acyclic task graphs (DAGs). In this paper, we present an efficient run-time system for executing general as...
We consider several natural broadcasting problems for the LogP model of distributed memory machines recently proposed by Culler et al. For each of these problems, we present algor...
Richard M. Karp, Abhijit Sahay, Eunice E. Santos, ...
A standard method for approximating averages in probabilistic models is to construct a Markov chain in the product space of the random variables with the desired equilibrium distr...
This paper is a report on experiences in benchmarking I/O performance on leading computational facilities on the NSF TeraGrid network with a large scale scientific application. In...