We introduce a network-based problem detection framework for distributed systems, which includes a data-mining method for discovering dynamic dependencies among distributed servic...
Large-scale distributed data management with P2P systems requires the existence of similarity operators for queries as we cannot assume that all users will agree on exactly the sa...
Consider a workload in which massively parallel tasks that require large resource pools are interleaved with short tasks that require fast response but consume fewer resources. We...
Mark Silberstein, Dan Geiger, Assaf Schuster, Miro...
The Lasso is a popular technique for joint estimation and continuous variable selection, especially well-suited for sparse and possibly under-determined linear regression problems....
The classical probabilistic models attempt to capture the Ad hoc information retrieval problem within a rigorous probabilistic framework. It has long been recognized that the prim...