784 citations · 861 across the 28 of their papers we have counts for
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A Multi-Task Approach to Robust Deep Reinforcement Learning for Resource Allocation
Steffen Gracla, Carsten Bockelmann, Armin Dekorsy
With increasing complexity of modern communication systems, machine learning algorithms have become a focal point of research. However, performance demands have tightened in parall…
On the Importance of Exploration for Real Life Learned Algorithms
Steffen Gracla, Carsten Bockelmann, Armin Dekorsy
The quality of data driven learning algorithms scales significantly with the quality of data available. One of the most straight-forward ways to generate good data is to sample or…
Robust Deep Reinforcement Learning Scheduling via Weight Anchoring
Steffen Gracla, Edgar Beck, Carsten Bockelmann +1
Questions remain on the robustness of data-driven learning methods when crossing the gap from simulation to reality. We utilize weight anchoring, a method known from continual lear…
Deep Reinforcement Model Selection for Communications Resource Allocation in On-Site Medical Care
Steffen Gracla, Edgar Beck, Carsten Bockelmann +1
Greater capabilities of mobile communications technology enable interconnection of on-site medical care at a scale previously unavailable. However, embedding such critical, demandi…