47 citations · 57 across the 9 of their papers we have counts for
Showing 2021Show all
3 papers · 1 filter
cs.LG2021
Exploring More When It Needs in Deep Reinforcement Learning
Youtian Guo, Qi Gao
We propose a exploration mechanism of policy in Deep Reinforcement Learning, which is exploring more when agent needs, called Add Noise to Noise (AN2N). The core idea is: when the…
cs.LG2021★ 2 cited
Gradient Importance Learning for Incomplete Observations
Qitong Gao, Dong Wang, Joshua D. Amason +6
Though recent works have developed methods that can generate estimates (or imputations) of the missing entries in a dataset to facilitate downstream analysis, most depend on assump…
cs.CR2021
Learning-Based Vulnerability Analysis of Cyber-Physical Systems
Amir Khazraei, Spencer Hallyburton, Qitong Gao +2
This work focuses on the use of deep learning for vulnerability analysis of cyber-physical systems (CPS). Specifically, we consider a control architecture widely used in CPS (e.g.,…