Preprocessing Under Uncertainty

Non-zero probability of nearest neighbor searching

Nearest Neighbor (NN) searching is a challenging problem in data management and has been widely studied in data mining, pattern recognition and computational geometry. The goal of NN searching is efficiently reporting the nearest data to a given object as a query. In most of the studies both the data and query are assumed to be precise, however, due to the real applications of NN searching, suc...

Minimum Spanning Tree under Explorable Uncertainty in Theory and Experiments

We consider the minimum spanning tree (MST) problem in an uncertainty model where uncertain edge weights can be explored at extra cost. The task is to find an MST by querying a minimum number of edges for their exact weight. This problem has received quite some attention from the algorithms theory community. In this paper, we conduct the first practical experiments for MST under uncertainty, th...

Preprocessing Under Uncertainty: Matroid Intersection

We continue the study of preprocessing under uncertainty that was initiated independently by Assadi et al. (FSTTCS 2015) and Fafianie et al. (STACS 2016). Here, we are given an instance of a tractable problem with a large static/known part and a small part that is dynamic/uncertain, and ask if there is an efficient algorithm that computes an instance of size polynomial in the uncertain part of ...

Improving Schedule Robustness via Stochastic Analysis and Dynamic Adaptation

We study methods that improve scheduling robustness under uncertain disturbances and dynamic shop conditions. A new method is proposed based on the notion of preprocessrst-schedule-later by Wu et al. [19]. Preprocessing starts at the beginning of the planning period where we use a Lagrangean Relaxation of the scheduling model to form networkstructured job subproblems. For each job subproblem we...

Strategic Technology Adoption under Technological Uncertainty

Leveraging observation uncertainty for robust visual tracking

In this paper, the accuracy of visual tracking is enhanced by leveraging a novel measure for observation quality. We measure observation quality with mutual information, then look at the interval covered by that mutual information. As observation uncertainty the interval length is proposed. The best observation is considered the one that both maximizes the observation quality and minimizes the ...