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cs.LG2023
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…
cs.LG2023
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…
cs.LG2023
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…