We present an adaptation technique for statistical machine translation, which applies the well-known Bayesian learning paradigm for adapting the model parameters. Since state-of-t...
In a pervasive computing environment, one is facing the problem of handling heterogeneous data from different sources, transmitted over heterogeneous channels and presented on het...
An emerging challenge in modern distributed querying is to efficiently process multiple continuous aggregation queries simultaneously. Processing each query independently may be i...
Ryan Huebsch, Minos N. Garofalakis, Joseph M. Hell...
High-level understanding of data must involve the interplay between substantial prior knowledge with geometric and statistical techniques. Our approach emphasizes the recovery of ...
We present a programming language model of the ideas behind Functional Adaptive Programming (AP-F) and our Java implementation, DemeterF. Computation in AP-F is encapsulated in se...