no code implementations • 7 Sep 2022 • Nicholas A. Ketz, Praveen K. Pilly
The robustness of any machine learning solution is fundamentally bound by the data it was trained on.
Model-based Reinforcement Learning reinforcement-learning +2
1 code implementation • 30 Oct 2021 • Eseoghene Ben-Iwhiwhu, Jeffery Dick, Nicholas A. Ketz, Praveen K. Pilly, Andrea Soltoggio
Meta-reinforcement learning (meta-RL) algorithms enable agents to adapt quickly to tasks from few samples in dynamic environments.
no code implementations • ICLR 2020 • Soheil Kolouri, Nicholas A. Ketz, Andrea Soltoggio, Praveen K. Pilly
Deep neural networks suffer from the inability to preserve the learned data representation (i. e., catastrophic forgetting) in domains where the input data distribution is non-stationary, and it changes during training.