13 citations · 16 across the 4 of their papers we have counts for
6 papers
Range-Coder with fast Adaptation and Table-Based Decoding
Tilo Strutz, Roman Rischke
The transmission or storage of signals typically involves data compression. The final processing step in compression systems is generally an entropy coding stage, which converts sy…
FedAUXfdp: Differentially Private One-Shot Federated Distillation
Haley Hoech, Roman Rischke, Karsten Müller +1
Federated learning suffers in the case of non-iid local datasets, i.e., when the distributions of the clients' data are heterogeneous. One promising approach to this challenge is t…
FedAUX: Leveraging Unlabeled Auxiliary Data in Federated Learning
Felix Sattler, Tim Korjakow, Roman Rischke +1
Federated Distillation (FD) is a popular novel algorithmic paradigm for Federated Learning, which achieves training performance competitive to prior parameter averaging based metho…
Communication-Efficient Federated Distillation
Felix Sattler, Arturo Marban, Roman Rischke +1
Communication constraints are one of the major challenges preventing the wide-spread adoption of Federated Learning systems. Recently, Federated Distillation (FD), a new algorithmi…
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…
Scheduling Maintenance Jobs in Networks
Fidaa Abed, Lin Chen, Yann Disser +5
We investigate the problem of scheduling the maintenance of edges in a network, motivated by the goal of minimizing outages in transportation or telecommunication networks. We focu…