most citedMulti-Modal Mutual Information (MuMMI) Training for Robust Self-Supervised Deep Reinforcement Learning

2 citations · 2 across the 3 of their papers we have counts for

collaborators

3 papers

cs.LG2021★ 2 cited

Multi-Modal Mutual Information (MuMMI) Training for Robust Self-Supervised Deep Reinforcement Learning

Kaiqi Chen, Yong Lee, Harold Soh

This work focuses on learning useful and robust deep world models using multiple, possibly unreliable, sensors. We find that current methods do not sufficiently encourage a shared…

cs.RO2021

Collaborative Visual Inertial SLAM for Multiple Smart Phones

Jialing Liu, Ruyu Liu, Kaiqi Chen +2

The efficiency and accuracy of mapping are crucial in a large scene and long-term AR applications. Multi-agent cooperative SLAM is the precondition of multi-user AR interaction. Th…

cs.LG2020

Improving Layer-wise Adaptive Rate Methods using Trust Ratio Clipping

Jeffrey Fong, Siwei Chen, Kaiqi Chen

Training neural networks with large batch is of fundamental significance to deep learning. Large batch training remarkably reduces the amount of training time but has difficulties…