We consider a system of compute and storage resources geographically distributed over a large number of locations connected via a wide-area network. By distributing the resources,...
Moritz Steiner, Bob Gaglianello Gaglianello, Vijay...
Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of...
Michael Collins, Amir Globerson, Terry Koo, Xavier...
Performance of distributed applications largely depends on the mapping of their components on the underlying architecture. On one mponent-based approaches provide an abstraction su...
Sampling is an important tool for estimating large, complex sums and integrals over highdimensional spaces. For instance, importance sampling has been used as an alternative to ex...
The advent of large scale multi-hop wireless networks highlights problems of fault tolerance and scale in distributed system, motivating designs that autonomously recover from tra...