33 citations · 105 across the 27 of their papers we have counts for
4 papers · 1 filter
Truth Inference at Scale: A Bayesian Model for Adjudicating Highly Redundant Crowd Annotations
Yuan Li, Benjamin I. P. Rubinstein, Trevor Cohn
Crowd-sourcing is a cheap and popular means of creating training and evaluation datasets for machine learning, however it poses the problem of `truth inference', as individual work…
A Note on Bounding Regret of the CUCB Contextual Combinatorial Bandit
Bastian Oetomo, Malinga Perera, Renata Borovica-Gajic +1
We revisit the proof by Qin et al. (2014) of bounded regret of the CUCB contextual combinatorial bandit. We demonstrate an error in the proof of volumetric expansion of the mom…
Adversarial Reinforcement Learning under Partial Observability in Autonomous Computer Network Defence
Yi Han, David Hubczenko, Paul Montague +6
Recent studies have demonstrated that reinforcement learning (RL) agents are susceptible to adversarial manipulation, similar to vulnerabilities previously demonstrated in the supe…
Differentially-Private Two-Party Egocentric Betweenness Centrality
Leyla Roohi, Benjamin I. P. Rubinstein, Vanessa Teague
We describe a novel protocol for computing the egocentric betweenness centrality of a node when relevant edge information is spread between two mutually distrusting parties such as…