7 citations · 13 across the 11 of their papers we have counts for
3 papers · 1 filter
Scaling Compute Is Not All You Need for Adversarial Robustness
Edoardo Debenedetti, Zishen Wan, Maksym Andriushchenko +3
The last six years have witnessed significant progress in adversarially robust deep learning. As evidenced by the CIFAR-10 dataset category in RobustBench benchmark, the accuracy u…
FRL-FI: Transient Fault Analysis for Federated Reinforcement Learning-Based Navigation Systems
Zishen Wan, Aqeel Anwar, Abdulrahman Mahmoud +4
Swarm intelligence is being increasingly deployed in autonomous systems, such as drones and unmanned vehicles. Federated reinforcement learning (FRL), a key swarm intelligence para…
QuaRL: Quantization for Fast and Environmentally Sustainable Reinforcement Learning
Srivatsan Krishnan, Maximilian Lam, Sharad Chitlangia +4
Deep reinforcement learning continues to show tremendous potential in achieving task-level autonomy, however, its computational and energy demands remain prohibitively high. In thi…