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Unlocking High-Accuracy Differentially Private Image Classification through Scale


Apr 28, 2022
Soham De, Leonard Berrada, Jamie Hayes, Samuel L. Smith, Borja Balle


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Reconstructing Training Data with Informed Adversaries


Jan 13, 2022
Borja Balle, Giovanni Cherubin, Jamie Hayes


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Learning to be adversarially robust and differentially private


Jan 06, 2022
Jamie Hayes, Borja Balle, M. Pawan Kumar

* Preliminary work appeared at PPML 2021 

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Ethical and social risks of harm from Language Models


Dec 08, 2021
Laura Weidinger, John Mellor, Maribeth Rauh, Conor Griffin, Jonathan Uesato, Po-Sen Huang, Myra Cheng, Mia Glaese, Borja Balle, Atoosa Kasirzadeh, Zac Kenton, Sasha Brown, Will Hawkins, Tom Stepleton, Courtney Biles, Abeba Birhane, Julia Haas, Laura Rimell, Lisa Anne Hendricks, William Isaac, Sean Legassick, Geoffrey Irving, Iason Gabriel


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A Law of Robustness for Weight-bounded Neural Networks


Mar 12, 2021
Hisham Husain, Borja Balle

* The main result does not resolve the conjecture as claimed. However the proof technique can be used to obtain a weaker result. The manuscript will be updated at a later date 

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Private Reinforcement Learning with PAC and Regret Guarantees


Sep 18, 2020
Giuseppe Vietri, Borja Balle, Akshay Krishnamurthy, Zhiwei Steven Wu


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Privacy Amplification via Random Check-Ins


Jul 30, 2020
Borja Balle, Peter Kairouz, H. Brendan McMahan, Om Thakkar, Abhradeep Thakurta

* Updated proof for $(\epsilon_0, \delta_0)$-DP local randomizers 

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Privacy- and Utility-Preserving Textual Analysis via Calibrated Multivariate Perturbations


Oct 20, 2019
Oluwaseyi Feyisetan, Borja Balle, Thomas Drake, Tom Diethe

* Accepted at WSDM 2020 

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