6 citations · 10 across the 4 of their papers we have counts for
6 papers
Sorting and Hypergraph Orientation under Uncertainty with Predictions
Thomas Erlebach, Murilo Santos de Lima, Nicole Megow +1
Learning-augmented algorithms have been attracting increasing interest, but have only recently been considered in the setting of explorable uncertainty where precise values of unce…
Learning-Augmented Query Policies for Minimum Spanning Tree with Uncertainty
Thomas Erlebach, Murilo Santos de Lima, Nicole Megow +1
We study how to utilize (possibly erroneous) predictions in a model for computing under uncertainty in which an algorithm can query unknown data. Our aim is to minimize the number…
Orienting (hyper)graphs under explorable stochastic uncertainty
Evripidis Bampis, Christoph Dürr, Thomas Erlebach +3
Given a hypergraph with uncertain node weights following known probability distributions, we study the problem of querying as few nodes as possible until the identity of a node wit…
Query-Competitive Sorting with Uncertainty
Magnús M. Halldórsson, Murilo S. de Lima
We study the problem of sorting under incomplete information, when queries are used to resolve uncertainties. Each of data items has an unknown value, which is known to lie in…
Learning-Augmented Query Policies
Thomas Erlebach, Murilo S. de Lima, Nicole Megow +1
We study how to utilize (possibly machine-learned) predictions in a model for computing under uncertainty in which an algorithm can query unknown data. The goal is to minimize the…
Query Minimization under Stochastic Uncertainty
Steven Chaplick, Magnús M. Halldórsson, Murilo S. de Lima +1
We study problems with stochastic uncertainty information on intervals for which the precise value can be queried by paying a cost. The goal is to devise an adaptive decision tree…