9 citations · 9 across the 1 of their papers we have counts for
2 papers
cs.LG2022★ 9 cited
Adversarial Training for High-Stakes Reliability
Daniel M. Ziegler, Seraphina Nix, Lawrence Chan +9
In the future, powerful AI systems may be deployed in high-stakes settings, where a single failure could be catastrophic. One technique for improving AI safety in high-stakes setti…
cs.LG2016
On the Detection of Mixture Distributions with applications to the Most Biased Coin Problem
Kevin Jamieson, Daniel Haas, Ben Recht
This paper studies the trade-off between two different kinds of pure exploration: breadth versus depth. The most biased coin problem asks how many total coin flips are required to…