Learning dynamic Bayesian network structures provides a principled mechanism for identifying conditional dependencies in time-series data. An important assumption of traditional D...
Abstract—Unmanned aerial vehicles (UAVs) represent an important class of networked robotic applications that must be both highly dependable and autonomous. This paper addresses s...
Forecasting is of prime importance for accuracy in decision making. For data sets containing high autocorrelations, failure to account for temporal dependence will result in poor ...
We describe a generator for hierarchical problems called the Hierarchical Problem Generator (HPG). Hierarchical problems are of interest since they constitute a class of problems ...
Edwin D. de Jong, Richard A. Watson, Dirk Thierens
We study the integral uniform (multicommodity) flow problem in a graph G and construct a fractional solution whose properties are invariant under the action of a group of automorp...