We present an ensemble learning approach that achieves accurate predictions from arbitrarily partitioned data. The partitions come from the distributed processing requirements of ...
Larry Shoemaker, Robert E. Banfield, Lawrence O. H...
It is widely acknowledged that coordination of large scale software development is an extremely difficult and persistent problem. Since the structure of the code mirrors the struc...
There has been significant recent progress in reasoning and constraint processing methods. In areas such as planning and finite model-checking, current solution techniques can h...
act 11 We describe an ensemble approach to learning from arbitrarily partitioned data. The partitioning comes from the distributed process12 ing requirements of a large scale simul...
Larry Shoemaker, Robert E. Banfield, Lawrence O. H...
We present Grouped Distributed Queues (GDQ), the first proportional share scheduler for multiprocessor systems that scales well with a large number of processors and processes. G...