3 citations · 5 across the 8 of their papers we have counts for
4 papers · 1 filter
Automatic Optimisation of Normalised Neural Networks
Namhoon Cho, Hyo-Sang Shin
We propose automatic optimisation methods considering the geometry of matrix manifold for the normalised parameters of neural networks. Layerwise weight normalisation with respect…
Robust Recurrent Reinforcement Learning under Evolving Hidden Disturbances with Application to Rover Wheel Slip
Saki Omi, Hyo-Sang Shin, Namhoon Cho +2
Reinforcement learning (RL) performs well in continuous-control tasks, but evolving hidden disturbances create partial observability: the agent must infer decision-relevant latent…
Bayesian Learning Approach to Model Predictive Control
Namhoon Cho, Seokwon Lee, Hyo-Sang Shin +1
This study presents a Bayesian learning perspective towards model predictive control algorithms. High-level frameworks have been developed separately in the earlier studies on Baye…
Optimisation of Structured Neural Controller Based on Continuous-Time Policy Gradient
Namhoon Cho, Hyo-Sang Shin
This study presents a policy optimisation framework for structured nonlinear control of continuous-time (deterministic) dynamic systems. The proposed approach prescribes a structur…