We use unsupervised probabilistic machine learning ideas to try to explain the kinds of learning observed in real neurons, the goal being to connect abstract principles of self-or...
This paper describes a hidden Markov model (HMM) based approach to perform search interface segmentation. Automatic processing of an interface is a must to access the invisible co...
The problem of identifying approximately duplicate records in databases is an essential step for data cleaning and data integration processes. Most existing approaches have relied...
We analyze the performance of protocols for load balancing in distributed systems based on no-regret algorithms from online learning theory. These protocols treat load balancing a...
Numerous systems have been designed which use virtualization to subdivide the ample resources of a modern computer. Some require specialized hardware, or cannot support commodity ...
Paul Barham, Boris Dragovic, Keir Fraser, Steven H...