Search Results for author: Jonathan Lebensold

Found 6 papers, 2 papers with code

DP-RDM: Adapting Diffusion Models to Private Domains Without Fine-Tuning

1 code implementation21 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.

Memorization Retrieval

On the Privacy of Selection Mechanisms with Gaussian Noise

1 code implementation9 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.

Actor Critic with Differentially Private Critic

no code implementations14 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.

reinforcement-learning Reinforcement Learning (RL) +1

Neural Transfer Learning for Cry-based Diagnosis of Perinatal Asphyxia

no code implementations24 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.

Transfer Learning

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