Embedding algorithms search for low dimensional structure in complex data, but most algorithms only handle objects of a single type for which pairwise distances are specified. Thi...
Amir Globerson, Gal Chechik, Fernando C. Pereira, ...
We consider the problem of storing an ordered dictionary data structure over a distributed set of nodes. In contrast to traditional sequential data structures, distributed data st...
Scalability is the primary challenge to studying large complex network systems with network emulation. This paper studies topology partitioning, assigning disjoint pieces of the n...
Ken Yocum, Ethan Eade, Julius Degesys, David Becke...
Bayesian networks are graphical representations of probability distributions. In virtually all of the work on learning these networks, the assumption is that we are presented with...
Procedural representations of control policies have two advantages when facing the scale-up problem in learning tasks. First they are implicit, with potential for inductive genera...