no code implementations • 21 Mar 2024 • Jonathan Lebensold, Maziar Sanjabi, Pietro Astolfi, Adriana Romero-Soriano, Kamalika Chaudhuri, Mike Rabbat, Chuan Guo
Text-to-image diffusion models have been shown to suffer from sample-level memorization, possibly reproducing near-perfect replica of images that they are trained on, which may be undesirable.
1 code implementation • 9 Feb 2024 • Jonathan Lebensold, Doina Precup, Borja Balle
In this work, we revisit the analysis of Report Noisy Max and Above Threshold with Gaussian noise and show that, under the additional assumption that the underlying queries are bounded, it is possible to provide pure ex-ante DP bounds for Report Noisy Max and pure ex-post DP bounds for Above Threshold.
no code implementations • 14 Dec 2021 • Shahar Avin, Haydn Belfield, Miles Brundage, Gretchen Krueger, Jasmine Wang, Adrian Weller, Markus Anderljung, Igor Krawczuk, David Krueger, Jonathan Lebensold, Tegan Maharaj, Noa Zilberman
The range of application of artificial intelligence (AI) is vast, as is the potential for harm.
no code implementations • 14 Oct 2019 • Jonathan Lebensold, William Hamilton, Borja Balle, Doina Precup
Reinforcement learning algorithms are known to be sample inefficient, and often performance on one task can be substantially improved by leveraging information (e. g., via pre-training) on other related tasks.
no code implementations • 24 Jun 2019 • Charles C. Onu, Jonathan Lebensold, William L. Hamilton, Doina Precup
Despite continuing medical advances, the rate of newborn morbidity and mortality globally remains high, with over 6 million casualties every year.