Policy gradient (PG) reinforcement learning algorithms have strong (local) convergence guarantees, but their learning performance is typically limited by a large variance in the e...
Developing Data Grids has increasingly become a major concern to make Grids attractive for a wide range of data-intensive applications. Storage subsystems are most likely to be a ...
This paper discusses our experience in building SPIRE, an autonomic system for service provision. The architecture consists of a set of hosted Web Services subject to QoS constrain...
While traditional database systems optimize for performance on one-shot queries, emerging large-scale monitoring applications require continuous tracking of complex aggregates and...
Graham Cormode, Minos N. Garofalakis, S. Muthukris...
We compare the performance of five well-known truncation heuristics for mitigating the effects of initialization bias in the output analysis of steady-state simulations. Two of th...
K. Preston White, Michael J. Cobb, Stephen C. Spra...