In optimization or machine learning problems we are given a set of items, usually points in
some metric space, and the goal is to minimize or maximize an objective function over some …

Betweenness centrality is a fundamental measure in social network analysis, expressing the
importance or influence of individual vertices in a network in terms of the fraction of shortest …

ABPA Ξ A Σ (ABRAXAS): Gnostic word of mystic meaning. We present ABRA, a suite of
algorithms to compute and maintain probabilistically guaranteed high-quality …

We present MaNIACS, a sampling-based randomized algorithm for computing high-quality
approximations of the collection of the subgraph patterns that are frequent in a single, large …

Sometimes an autonomous vehicle realizes that unfortunately a crash will come about;
however there are several possible crashes and the autonomous vehicle can still make a …

The Trolley Problem Version of Autonomous Vehicles Home Editorial Board Open
Transportation Journal Open Transportation Journal Quick Search anywhere Enter Search …

Starting with a similarity function between objects, it is possible to define a distance metric
(the kernel distance) on pairs of objects, and more generally on probability distributions over …

The tasks of extracting (top-K) Frequent Itemsets (FIs) and Association Rules (ARs) are
fundamental primitives in data mining and database applications. Exact algorithms for these …

A system for a real-time estimation of vehicle accident potential damages is proposed with
the aim of facilitating autonomous vehicle's embedded computer system to come to the least …

We study the complexity of geometric minimum spanning trees under a stochastic model of
input: Suppose we are given a master set of points s1, s_2,..., sn in d-dimensional Euclidean …