Skyline computation is widely used in multi-criteria decision making. As research in uncertain databases draws increasing attention, skyline queries with uncertain data have also ...
Probabilistic relational models are an efficient way to learn and represent the dynamics in realistic environments consisting of many objects. Autonomous intelligent agents that gr...
Motivated by the increasing need to analyze complex, uncertain multidimensional data this paper proposes probabilistic OLAP queries that are computed using probability distributio...
Igor Timko, Curtis E. Dyreson, Torben Bach Pederse...
A low-degree test is a collection of simple, local rules for checking the proximity of an arbitrary function to a lowdegree polynomial. Each rule depends on the function’s value...
Unifying first-order logic and probability is a long-standing goal of AI, and in recent years many representations combining aspects of the two have been proposed. However, infere...