Distributed averaging describes a class of network algorithms for the decentralized computation of aggregate statistics. Initially, each node has a scalar data value, and the goal...
We analyze the application of ensemble learning to recommender systems on the Netflix Prize dataset. For our analysis we use a set of diverse state-of-the-art collaborative filt...
Software systems evolve over time due to changes in requirements, optimization of code, fixes for security and reliability bugs etc. Code churn, which measures the changes made to...
The real-time scheduling advisor (RTSA) is an entirely userlevel system that an application running on a typical shared, unreserved distributed computing environment can turn to f...
Several predictive systems are nowadays vital for operations and decision support. The quality of these systems is most of the time defined by their average accuracy which has lo...