In this paper we propose a genetic programming approach to learning stochastic models with unsymmetrical noise distributions. Most learning algorithms try to learn from noisy data...
We introduce and validate bootstrap techniques to compute confidence intervals that quantify the effect of test-collection variability on average precision (AP) and mean average...
This paper describes Rthreads (Remote threads), a software distributed shared memory system that supports sharing of global variables on clusters of computers with physically dist...
Accessing data from numerous widely-distributed sources poses signi cant new challenges for query optimization and execution. Congestion and failures in the network can introduce ...
Laurent Amsaleg, Michael J. Franklin, Anthony Toma...
AspectJ-like languages are currently ineffective at modularizing heterogeneous concerns that are tightly coupled to the source code of the base program, such as logging, invariant...