Bassily, Raef

28 publications

ICML 2025 Private Model Personalization Revisited Conor Snedeker, Xinyu Zhou, Raef Bassily

ICML 2024 Differentially Private Domain Adaptation with Theoretical Guarantees Raef Bassily, Corinna Cortes, Anqi Mao, Mehryar Mohri

ALT 2024 Differentially Private Non-Convex Optimization Under the KL Condition with Optimal Rates Michael Menart, Enayat Ullah, Raman Arora, Raef Bassily, Cristobal Guzman

ICML 2024 Differentially Private Worst-Group Risk Minimization Xinyu Zhou, Raef Bassily

NeurIPS 2024 Private Algorithms for Stochastic Saddle Points and Variational Inequalities: Beyond Euclidean Geometry Raef Bassily, Cristóbal Guzmán, Michael Menart

NeurIPS 2024 Public-Data Assisted Private Stochastic Optimization: Power and Limitations Enayat Ullah, Michael Menart, Raef Bassily, Cristóbal Guzmán, Raman Arora

COLT 2023 Differentially Private Algorithms for the Stochastic Saddle Point Problem with Optimal Rates for the Strong Gap Raef Bassily, Cristóbal Guzmán, Michael Menart

ICML 2023 Faster Rates of Convergence to Stationary Points in Differentially Private Optimization Raman Arora, Raef Bassily, Tomás González, Cristóbal A Guzmán, Michael Menart, Enayat Ullah

AISTATS 2023 Principled Approaches for Private Adaptation from a Public Source Raef Bassily, Mehryar Mohri, Ananda Theertha Suresh

ICML 2023 User-Level Private Stochastic Convex Optimization with Optimal Rates Raef Bassily, Ziteng Sun

NeurIPS 2022 Differentially Private Generalized Linear Models Revisited Raman Arora, Raef Bassily, Cristóbal Guzmán, Michael Menart, Enayat Ullah

NeurIPS 2022 Differentially Private Learning with Margin Guarantees Raef Bassily, Mehryar Mohri, Ananda Theertha Suresh

COLT 2022 Open Problem: Better Differentially Private Learning Algorithms with Margin Guarantees Raef Bassily, Mehryar Mohri, Ananda Theertha Suresh

NeurIPS 2022 Task-Level Differentially Private Meta Learning Xinyu Zhou, Raef Bassily

NeurIPS 2021 Differentially Private Stochastic Optimization: New Results in Convex and Non-Convex Settings Raef Bassily, Cristóbal Guzmán, Michael Menart

COLT 2021 Non-Euclidean Differentially Private Stochastic Convex Optimization Raef Bassily, Cristobal Guzman, Anupama Nandi

NeurIPS 2020 Learning from Mixtures of Private and Public Populations Raef Bassily, Shay Moran, Anupama Nandi

JMLR 2020 Practical Locally Private Heavy Hitters Raef Bassily, Kobbi Nissim, Uri Stemmer, Abhradeep Thakurta

ICML 2020 Private Query Release Assisted by Public Data Raef Bassily, Albert Cheu, Shay Moran, Aleksandar Nikolov, Jonathan Ullman, Steven Wu

ALT 2020 Privately Answering Classification Queries in the Agnostic PAC Model Anupama Nandi, Raef Bassily

NeurIPS 2020 Stability of Stochastic Gradient Descent on Nonsmooth Convex Losses Raef Bassily, Vitaly Feldman, Cristóbal Guzmán, Kunal Talwar

NeurIPS 2019 Limits of Private Learning with Access to Public Data Noga Alon, Raef Bassily, Shay Moran

AISTATS 2019 Linear Queries Estimation with Local Differential Privacy Raef Bassily

NeurIPS 2019 Private Stochastic Convex Optimization with Optimal Rates Raef Bassily, Vitaly Feldman, Kunal Talwar, Abhradeep Guha Thakurta

ALT 2018 Learners That Use Little Information Raef Bassily, Shay Moran, Ido Nachum, Jonathan Shafer, Amir Yehudayoff

NeurIPS 2018 Model-Agnostic Private Learning Raef Bassily, Om Thakkar, Abhradeep Guha Thakurta

ICML 2018 The Power of Interpolation: Understanding the Effectiveness of SGD in Modern Over-Parametrized Learning Siyuan Ma, Raef Bassily, Mikhail Belkin

NeurIPS 2017 Practical Locally Private Heavy Hitters Raef Bassily, Kobbi Nissim, Uri Stemmer, Abhradeep Guha Thakurta