In this work, we present an approach to supervisory reinforcement learni...
In this paper, we leverage ideas from model-based control to address the...
Transformers have become a predominant machine learning workload, they a...
This paper discusses an Enhanced Model-Agnostic Meta-Learning (E-MAML)
a...
Faults are endemic to all systems. Adaptive fault-tolerant control maint...
We propose a novel adaptive reinforcement learning control approach for ...
A desirable property in fault-tolerant controllers is adaptability to sy...
Current methods for authentication based on public-key cryptography are
...