I. Two

most citedDeep hierarchical reinforcement agents for automated penetration testing

23 citations · 25 across the 2 of their papers we have counts for

collaborators

3 papers

cs.AI2021★ 23 cited

Deep hierarchical reinforcement agents for automated penetration testing

Khuong Tran, Ashlesha Akella, Maxwell Standen +4

Penetration testing the organised attack of a computer system in order to test existing defences has been used extensively to evaluate network security. This is a time consuming pr…

hep-ex2021★ 2 cited

An overview of $η_{c} (1 S)$ , $η_{c} (2 S)$ and $h_{c} (1 P)$ physics at BESIII

Qingping Ji, Shuangshi Fang, Zhiyong Wang

With the help of the largest data samples of $J / ψ$ and $ψ (2 S)$ events ever produced in $e^{+} e^{-}$ annihilations, the three singlet charmonium states, $η_{c} (1 S)$ , $η_{c} (2 S)$ and $h_c(1P…

cs.LG2020

GLISTER: Generalization based Data Subset Selection for Efficient and Robust Learning

Krishnateja Killamsetty, Durga Sivasubramanian, Ganesh Ramakrishnan +1

Large scale machine learning and deep models are extremely data-hungry. Unfortunately, obtaining large amounts of labeled data is expensive, and training state-of-the-art models (w…

Deep hierarchical reinforcement agents for automated penetration testing

An overview of ηc​(1S), ηc​(2S) and hc​(1P) physics at BESIII

GLISTER: Generalization based Data Subset Selection for Efficient and Robust Learning

An overview of $η_{c} (1 S)$ , $η_{c} (2 S)$ and $h_{c} (1 P)$ physics at BESIII