Massive-scale distributed computing is a challenge at our doorstep. The current exponential growth of data calls for massive-scale capabilities of storage and processing. This is b...
Very large scale computations are now becoming routinely used as a methodology to undertake scientific research. In this context, ‘provenance systems’ are regarded as the equ...
Paul T. Groth, Simon Miles, Weijian Fang, Sylvia C...
Random walk graph and Markov chain based models are used heavily in many data and system analysis domains, including web, bioinformatics, and queuing. These models enable the desc...
We propose a new unsupervised learning technique for extracting information from large text collections. We model documents as if they were generated by a two-stage stochastic pro...
Mark Steyvers, Padhraic Smyth, Michal Rosen-Zvi, T...
Data access prediction has been proposed as a mechanism to overcome latency lag, and more recently as a means of conserving energy in mobile systems. We present a fully adaptive p...
James Larkby-Lahet, Ganesh Santhanakrishnan, Ahmed...