5 citations · 10 across the 5 of their papers we have counts for
9 papers
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…
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…
Online Minimum Cost Matching on the Line with Recourse
Nicole Megow, Lukas Nölke
In online minimum cost matching on the line, requests appear one by one and have to be matched immediately and irrevocably to a given set of servers, all on the real line. The…
Energy Minimization in DAG Scheduling on MPSoCs at Run-Time: Theory and Practice
Bertrand Simon, Joachim Falk, Nicole Megow +1
Static (offline) techniques for mapping applications given by task graphs to MPSoC systems often deliver overly pessimistic and thus suboptimal results w.r.t. exploiting time slack…
Optimal Algorithms for Scheduling under Time-of-Use Tariffs
Lin Chen, Nicole Megow, Roman Rischke +2
We consider a natural generalization of classical scheduling problems in which using a time unit for processing a job causes some time-dependent cost which must be paid in addition…
A general framework for handling commitment in online throughput maximization
Lin Chen, Franziska Eberle, Nicole Megow +2
We study a fundamental online job admission problem where jobs with deadlines arrive online over time at their release dates, and the task is to determine a preemptive single-serve…