A new achievable ergodic secrecy rate region for the fading multiple access wiretap channel. - Raef Bassily; Sennur Ulukus (Allerton, 2009)

Ergodic Secret Alignment for the Fading Multiple Access Wiretap Channel. - Raef Bassily; Sennur Ulukus (ICC, 2010)

Deaf cooperation for secrecy in multiple-relay networks. - Raef Bassily; Sennur Ulukus (GLOBECOM Workshops, 2011)

Deaf cooperation for secrecy with a multi-antenna helper. - Raef Bassily; Sennur Ulukus (CISS, 2012)

Decode-and-Forward based strategies for secrecy in multiple-relay networks. - Raef Bassily; Sennur Ulukus (WCNC, 2012)

Secure communication in multiple relay networks through decode-and-forward strategies. - Raef Bassily; Sennur Ulukus (J. Commun. Networks, 2012)

Deaf Cooperation for Secrecy With Multiple Antennas at the Helper. - Raef Bassily; Sennur Ulukus (IEEE Trans. Inf. Forensics Secur., 2012)

Ergodic Secret Alignment. - Raef Bassily; Sennur Ulukus (IEEE Trans. Inf. Theory, 2012)

Coupled-Worlds Privacy: Exploiting Adversarial Uncertainty in Statistical Data Privacy. - Raef Bassily; Adam Groce; Jonathan Katz; Adam D. Smith 001 (FOCS, 2013)

Cooperative Security at the Physical Layer: A Summary of Recent Advances. - Raef Bassily; Ersen Ekrem; Xiang He 001; Ender Tekin; Jianwei Xie; Matthieu R. Bloch; Sennur Ulukus; Aylin Yener (IEEE Signal Process. Mag., 2013)

Deaf Cooperation and Relay Selection Strategies for Secure Communication in Multiple Relay Networks. - Raef Bassily; Sennur Ulukus (IEEE Trans. Signal Process., 2013)

Private Empirical Risk Minimization: Efficient Algorithms and Tight Error Bounds. - Raef Bassily; Adam D. Smith 001; Abhradeep Thakurta (FOCS, 2014)

Causal Erasure Channels. - Raef Bassily; Adam D. Smith 001 (SODA, 2014)

Private Empirical Risk Minimization, Revisited. - Raef Bassily; Adam D. Smith 001; Abhradeep Thakurta (CoRR, 2014)

Local, Private, Efficient Protocols for Succinct Histograms. - Raef Bassily; Adam D. Smith 001 (STOC, 2015)

Typicality-Based Stability and Privacy. - Raef Bassily; Yoav Freund (CoRR, 2016)

Learners that Leak Little Information. - Raef Bassily; Shay Moran; Ido Nachum; Jonathan Shafer; Amir Yehudayoff (CoRR, 2017)

Learners that Use Little Information. - Raef Bassily; Shay Moran; Ido Nachum; Jonathan Shafer; Amir Yehudayoff (ALT, 2018)

The Power of Interpolation: Understanding the Effectiveness of SGD in Modern Over-parametrized Learning. - Siyuan Ma; Raef Bassily; Mikhail Belkin (ICML, 2018)

Model-Agnostic Private Learning. - Raef Bassily; Abhradeep Guha Thakurta; Om Dipakbhai Thakkar (NeurIPS, 2018)

Differentially-private software analytics for mobile apps: opportunities and challenges. - Hailong Zhang 006; Sufian Latif; Raef Bassily; Atanas Rountev (SWAN@ESEC/SIGSOFT FSE, 2018)

Model-Agnostic Private Learning via Stability. - Raef Bassily; Om Thakkar 001; Abhradeep Thakurta (CoRR, 2018)

On exponential convergence of SGD in non-convex over-parametrized learning. - Raef Bassily; Mikhail Belkin; Siyuan Ma (CoRR, 2018)

Linear Queries Estimation with Local Differential Privacy. - Raef Bassily (AISTATS, 2019)

Private Stochastic Convex Optimization with Optimal Rates. - Raef Bassily; Vitaly Feldman; Kunal Talwar; Abhradeep Guha Thakurta (NeurIPS, 2019)

Limits of Private Learning with Access to Public Data. - Raef Bassily; Shay Moran; Noga Alon (NeurIPS, 2019)

Introducing Privacy in Screen Event Frequency Analysis for Android Apps. - Hailong Zhang 006; Sufian Latif; Raef Bassily; Atanas Rountev (SCAM, 2019)

Privately Answering Classification Queries in the Agnostic PAC Model. - Anupama Nandi; Raef Bassily (ALT, 2020)

A study of event frequency profiling with differential privacy. - Hailong Zhang 006; Yu Hao; Sufian Latif; Raef Bassily; Atanas Rountev (CC, 2020)

Private Query Release Assisted by Public Data. - Raef Bassily; Albert Cheu; Shay Moran; Aleksandar Nikolov; Jonathan R. Ullman; Zhiwei Steven Wu (ICML, 2020)

Introducing Differential Privacy Mechanisms for Mobile App Analytics of Dynamic Content. - Sufian Latif; Yu Hao; Hailong Zhang 006; Raef Bassily; Atanas Rountev (ICSME, 2020)

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

Learning from Mixtures of Private and Public Populations. - Raef Bassily; Shay Moran; Anupama Nandi (NeurIPS, 2020)

Differentially-Private Control-Flow Node Coverage for Software Usage Analysis. - Hailong Zhang 006; Sufian Latif; Raef Bassily; Atanas Rountev (USENIX Security Symposium, 2020)

Practical Locally Private Heavy Hitters. - Raef Bassily; Kobbi Nissim; Uri Stemmer; Abhradeep Thakurta (J. Mach. Learn. Res., 2020)

Differentially-private software frequency profiling under linear constraints. - Hailong Zhang 006; Yu Hao; Sufian Latif; Raef Bassily; Atanas Rountev (Proc. ACM Program. Lang., 2020)

Non-Euclidean Differentially Private Stochastic Convex Optimization. - Raef Bassily; Cristóbal Guzmán; Anupama Nandi (COLT, 2021)

Differential Privacy for Coverage Analysis of Software Traces. - Yu Hao; Sufian Latif; Hailong Zhang 006; Raef Bassily; Atanas Rountev (ECOOP, 2021)

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

Differential Privacy for Coverage Analysis of Software Traces (Artifact). - Yu Hao; Sufian Latif; Hailong Zhang 006; Raef Bassily; Atanas Rountev (Dagstuhl Artifacts Ser., 2021)

Algorithmic Stability for Adaptive Data Analysis. - Raef Bassily; Kobbi Nissim; Adam D. Smith 001; Thomas Steinke 002; Uri Stemmer; Jonathan R. Ullman (SIAM J. Comput., 2021)

Leveraging Synergies Between AI and Networking to Build Next Generation Edge Networks. - Sen Lin 001; Ming Shi 003; Anish Arora; Raef Bassily; Elisa Bertino; Constantine Caramanis; Kaushik R. Chowdhury; Eylem Ekici; Atilla Eryilmaz; Stratis Ioannidis; Nan Jiang 008; Gauri Joshi; et al. (CIC, 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 (NeurIPS, 2022)

Task-level Differentially Private Meta Learning. - Xinyu Zhou; Raef Bassily (NeurIPS, 2022)

Private Domain Adaptation from a Public Source. - Raef Bassily; Mehryar Mohri; Ananda Theertha Suresh (CoRR, 2022)

Principled Approaches for Private Adaptation from a Public Source. - Raef Bassily; Mehryar Mohri; Ananda Theertha Suresh (AISTATS, 2023)

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

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

User-level Private Stochastic Convex Optimization with Optimal Rates. - Raef Bassily; Ziteng Sun (ICML, 2023)

Differentially Private Non-Convex Optimization under the KL Condition with Optimal Rates. - Michael Menart; Enayat Ullah; Raman Arora; Raef Bassily; Cristóbal Guzmán (ALT, 2024)

Differentially Private Domain Adaptation with Theoretical Guarantees. - Raef Bassily; Corinna Cortes; Anqi Mao; Mehryar Mohri (ICML, 2024)

Differentially Private Worst-group Risk Minimization. - Xinyu Zhou; Raef Bassily (ICML, 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 (NeurIPS, 2024)

Private Model Personalization Revisited. - Conor Snedeker; Xinyu Zhou; Raef Bassily (CoRR, 2025)