All Netflix Prize algorithms proposed so far are prohibitively costly for large-scale production systems. In this paper, we describe an efficient dataflow implementation of a coll...
Srivatsava Daruru, Nena M. Marin, Matt Walker, Joy...
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...
In this paper, we propose a Quantified Distributed Constraint Optimization problem (QDCOP) that extends the framework of Distributed Constraint Optimization problems (DCOPs). DCOP...
Previous work in multiagent coordination has addressed the challenge of planning in domains where agents must optimize a global goal, while satisfying local resource constraints. ...
Emma Bowring, Zhengyu Yin, Rob Zinkov, Milind Tamb...
The explosion of data in the biological community demands the development of more scalable and flexible portals for bioinformatic computation. To address this need, we put forth c...
Rory Carmichael, Patrick Braga-Henebry, Douglas Th...