34 citations · 75 across the 8 of their papers we have counts for
3 papers · 1 filter
PEOPL: Characterizing Privately Encoded Open Datasets with Public Labels
Homa Esfahanizadeh, Adam Yala, Rafael G. L. D'Oliveira +8
Allowing organizations to share their data for training of machine learning (ML) models without unintended information leakage is an open problem in practice. A promising technique…
AI Gone Astray: Technical Supplement
Janice Yang, Ludvig Karstens, Casey Ross +1
This study is a technical supplement to "AI gone astray: How subtle shifts in patient data send popular algorithms reeling, undermining patient safety." from STAT News, which inves…
Syfer: Neural Obfuscation for Private Data Release
Adam Yala, Victor Quach, Homa Esfahanizadeh +5
Balancing privacy and predictive utility remains a central challenge for machine learning in healthcare. In this paper, we develop Syfer, a neural obfuscation method to protect aga…