11 citations · 30 across the 5 of their papers we have counts for
4 papers · 1 filter
Spectral Normalisation for Deep Reinforcement Learning: an Optimisation Perspective
Florin Gogianu, Tudor Berariu, Mihaela Rosca +3
Most of the recent deep reinforcement learning advances take an RL-centric perspective and focus on refinements of the training objective. We diverge from this view and show we can…
Continual Reinforcement Learning with Multi-Timescale Replay
Christos Kaplanis, Claudia Clopath, Murray Shanahan
In this paper, we propose a multi-timescale replay (MTR) buffer for improving continual learning in RL agents faced with environments that are changing continuously over time at ti…
Policy Consolidation for Continual Reinforcement Learning
Christos Kaplanis, Murray Shanahan, Claudia Clopath
We propose a method for tackling catastrophic forgetting in deep reinforcement learning that is \textit{agnostic} to the timescale of changes in the distribution of experiences, do…
A High GOPs/Slice Time Series Classifier for Portable and Embedded Biomedical Applications
Hamid Soleimani, Aliasghar, Makhlooghpour +3
Nowadays a diverse range of physiological data can be captured continuously for various applications in particular wellbeing and healthcare. Such data require efficient methods for…