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

Differentially Private Non-Convex Optimization under the KL Condition with Optimal Rates - Michael Menart; Enayat Ullah; Raman Arora; Raef Bassily; Cristóbal Guzmán (International Conference on Algorithmic Learning Theory, 25-28 February 2024, La Jolla, California, USA, 2024)

Differentially Private Domain Adaptation with Theoretical Guarantees - Raef Bassily; Corinna Cortes; Anqi Mao; Mehryar Mohri (Forty-first International Conference on Machine Learning, ICML 2024, Vienna, Austria, July 21-27, 2024, 2024)

Differentially Private Worst-group Risk Minimization - Xinyu Zhou; Raef Bassily (Forty-first International Conference on Machine Learning, ICML 2024, Vienna, Austria, July 21-27, 2024, 2024)

Private Algorithms for Stochastic Saddle Points and Variational Inequalities: Beyond Euclidean Geometry - Raef Bassily; Cristóbal Guzmán; Michael Menart (Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, NeurIPS 2024, Vancouver, BC, Canada, December 10 - 15, 2024, 2024)

Public-data Assisted Private Stochastic Optimization: Power and Limitations - Enayat Ullah; Michael Menart; Raef Bassily; Cristóbal Guzmán; Raman Arora (Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, NeurIPS 2024, Vancouver, BC, Canada, December 10 - 15, 2024, 2024)

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

Public-data Assisted Private Stochastic Optimization: Power and Limitations - Enayat Ullah; Michael Menart; Raef Bassily; Cristóbal Guzmán; Raman Arora (CoRR, 2024)

Private Algorithms for Stochastic Saddle Points and Variational Inequalities: Beyond Euclidean Geometry - Raef Bassily; Cristóbal Guzmán; Michael Menart (CoRR, 2024)

Principled Approaches for Private Adaptation from a Public Source - Raef Bassily; Mehryar Mohri; Ananda Theertha Suresh (International Conference on Artificial Intelligence and Statistics, 25-27 April 2023, Palau de Congressos, Valencia, Spain, 2023)

Differentially Private Algorithms for the Stochastic Saddle Point Problem with Optimal Rates for the Strong Gap - Raef Bassily; Cristóbal Guzmán; Michael Menart (The Thirty Sixth Annual Conference on Learning Theory, COLT 2023, 12-15 July 2023, Bangalore, India, 2023)

Faster Rates of Convergence to Stationary Points in Differentially Private Optimization - Raman Arora; Raef Bassily; Tomás González; Cristóbal Guzmán; Michael Menart; Enayat Ullah (International Conference on Machine Learning, ICML 2023, 23-29 July 2023, Honolulu, Hawaii, USA, 2023)

User-level Private Stochastic Convex Optimization with Optimal Rates - Raef Bassily; Ziteng Sun (International Conference on Machine Learning, ICML 2023, 23-29 July 2023, Honolulu, Hawaii, USA, 2023)

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

Differentially Private Domain Adaptation with Theoretical Guarantees - Raef Bassily; Corinna Cortes; Anqi Mao; Mehryar Mohri (CoRR, 2023)

Differentially Private Non-Convex Optimization under the KL Condition with Optimal Rates - Michael Menart; Enayat Ullah; Raman Arora; Raef Bassily; Cristóbal Guzmán (CoRR, 2023)

Leveraging Synergies Between AI and Networking to Build Next Generation Edge Networks - Sen Lin; Ming Shi; Anish Arora; Raef Bassily; Elisa Bertino; Constantine Caramanis; Kaushik R. Chowdhury; Eylem Ekici; Atilla Eryilmaz; Stratis Ioannidis; Nan Jiang; Gauri Joshi; et al. (8th IEEE International Conference on Collaboration and Internet Computing, CIC 2022, Atlanta, GA, USA, December 14-16, 2022, 2022)

Differentially Private Generalized Linear Models Revisited - Raman Arora; Raef Bassily; Cristóbal Guzmán; Michael Menart; Enayat Ullah (Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, NeurIPS 2022, New Orleans, LA, USA, November 28 - December 9, 2022, 2022)

Differentially Private Learning with Margin Guarantees - Raef Bassily; Mehryar Mohri; Ananda Theertha Suresh (Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, NeurIPS 2022, New Orleans, LA, USA, November 28 - December 9, 2022, 2022)

Task-level Differentially Private Meta Learning - Xinyu Zhou; Raef Bassily (Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, NeurIPS 2022, New Orleans, LA, USA, November 28 - December 9, 2022, 2022)

Differentially Private Learning with Margin Guarantees - Raef Bassily; Mehryar Mohri; Ananda Theertha Suresh (CoRR, 2022)

Differentially Private Generalized Linear Models Revisited - Raman Arora; Raef Bassily; Cristóbal Guzmán; Michael Menart; Enayat Ullah (CoRR, 2022)

Faster Rates of Convergence to Stationary Points in Differentially Private Optimization - Raman Arora; Raef Bassily; Tomás González; Cristóbal Guzmán; Michael Menart; Enayat Ullah (CoRR, 2022)

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

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

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

Non-Euclidean Differentially Private Stochastic Convex Optimization - Raef Bassily; Cristóbal Guzmán; Anupama Nandi (Conference on Learning Theory, COLT 2021, 15-19 August 2021, Boulder, Colorado, USA, 2021)

Differential Privacy for Coverage Analysis of Software Traces - Yu Hao; Sufian Latif; Hailong Zhang; Raef Bassily; Atanas Rountev (35th European Conference on Object-Oriented Programming, ECOOP 2021, July 11-17, 2021, Aarhus, Denmark (Virtual Conference), 2021)

Differentially Private Stochastic Optimization: New Results in Convex and Non-Convex Settings - Raef Bassily; Cristóbal Guzmán; Michael Menart (Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual, 2021)

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

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

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; Yu Hao; Sufian Latif; Raef Bassily; Atanas Rountev (Proc. ACM Program. Lang., 2020)

Privately Answering Classification Queries in the Agnostic PAC Model - Anupama Nandi; Raef Bassily (Algorithmic Learning Theory, ALT 2020, 8-11 February 2020, San Diego, CA, USA, 2020)

A study of event frequency profiling with differential privacy - Hailong Zhang; Yu Hao; Sufian Latif; Raef Bassily; Atanas Rountev (CC '20: 29th International Conference on Compiler Construction, San Diego, CA, USA, February 22-23, 2020, 2020)

Private Query Release Assisted by Public Data - Raef Bassily; Albert Cheu; Shay Moran; Aleksandar Nikolov; Jonathan R. Ullman; Zhiwei Steven Wu (Proceedings of the 37th International Conference on Machine Learning, ICML 2020, 13-18 July 2020, Virtual Event, 2020)

Introducing Differential Privacy Mechanisms for Mobile App Analytics of Dynamic Content - Sufian Latif; Yu Hao; Hailong Zhang; Raef Bassily; Atanas Rountev (IEEE International Conference on Software Maintenance and Evolution, ICSME 2020, Adelaide, Australia, September 28 - October 2, 2020, 2020)

Stability of Stochastic Gradient Descent on Nonsmooth Convex Losses - Raef Bassily; Vitaly Feldman; Cristóbal Guzmán; Kunal Talwar (Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual, 2020)

Learning from Mixtures of Private and Public Populations - Raef Bassily; Shay Moran; Anupama Nandi (Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual, 2020)

Differentially-Private Control-Flow Node Coverage for Software Usage Analysis - Hailong Zhang; Sufian Latif; Raef Bassily; Atanas Rountev (29th USENIX Security Symposium, USENIX Security 2020, August 12-14, 2020, 2020)

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

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

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

Linear Queries Estimation with Local Differential Privacy - Raef Bassily (The 22nd International Conference on Artificial Intelligence and Statistics, AISTATS 2019, 16-18 April 2019, Naha, Okinawa, Japan, 2019)

Limits of Private Learning with Access to Public Data - Raef Bassily; Shay Moran; Noga Alon (Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, December 8-14, 2019, Vancouver, BC, Canada, 2019)

Private Stochastic Convex Optimization with Optimal Rates - Raef Bassily; Vitaly Feldman; Kunal Talwar; Abhradeep Guha Thakurta (Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, December 8-14, 2019, Vancouver, BC, Canada, 2019)

Introducing Privacy in Screen Event Frequency Analysis for Android Apps - Hailong Zhang; Sufian Latif; Raef Bassily; Atanas Rountev (19th International Working Conference on Source Code Analysis and Manipulation, SCAM 2019, Cleveland, OH, USA, September 30 - October 1, 2019, 2019)

Privately Answering Classification Queries in the Agnostic PAC Model - Raef Bassily; Anupama Nandi (CoRR, 2019)

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

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

Learners that Use Little Information - Raef Bassily; Shay Moran; Ido Nachum; Jonathan Shafer; Amir Yehudayoff (Algorithmic Learning Theory, ALT 2018, 7-9 April 2018, Lanzarote, Canary Islands, Spain, 2018)

The Power of Interpolation: Understanding the Effectiveness of SGD in Modern Over-parametrized Learning - Siyuan Ma; Raef Bassily; Mikhail Belkin (Proceedings of the 35th International Conference on Machine Learning, ICML 2018, Stockholmsmässan, Stockholm, Sweden, July 10-15, 2018, 2018)

Model-Agnostic Private Learning - Raef Bassily; Abhradeep Guha Thakurta; Om Dipakbhai Thakkar (Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, NeurIPS 2018, December 3-8, 2018, Montréal, Canada, 2018)

Differentially-private software analytics for mobile apps: opportunities and challenges - Hailong Zhang; Sufian Latif; Raef Bassily; Atanas Rountev (Proceedings of the 4th ACM SIGSOFT International Workshop on Software Analytics, SWAN@ESEC/SIGSOFT FSE 2018, Lake Buena Vista, FL, USA, November 5, 2018, 2018)

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

Linear Queries Estimation with Local Differential Privacy - Raef Bassily (CoRR, 2018)

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

Practical Locally Private Heavy Hitters - Raef Bassily; Kobbi Nissim; Uri Stemmer; Abhradeep Guha Thakurta (Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, December 4-9, 2017, Long Beach, CA, USA, 2017)

Practical Locally Private Heavy Hitters - Raef Bassily; Kobbi Nissim; Uri Stemmer; Abhradeep Thakurta (CoRR, 2017)

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

The Power of Interpolation: Understanding the Effectiveness of SGD in Modern Over-parametrized Learning - Siyuan Ma; Raef Bassily; Mikhail Belkin (CoRR, 2017)

Algorithmic stability for adaptive data analysis - Raef Bassily; Kobbi Nissim; Adam D. Smith; Thomas Steinke; Uri Stemmer; Jonathan R. Ullman (Proceedings of the 48th Annual ACM SIGACT Symposium on Theory of Computing, STOC 2016, Cambridge, MA, USA, June 18-21, 2016, 2016)

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

Local, Private, Efficient Protocols for Succinct Histograms - Raef Bassily; Adam D. Smith (Proceedings of the Forty-Seventh Annual ACM on Symposium on Theory of Computing, STOC 2015, Portland, OR, USA, June 14-17, 2015, 2015)

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

Algorithmic Stability for Adaptive Data Analysis - Raef Bassily; Kobbi Nissim; Adam D. Smith; Thomas Steinke; Uri Stemmer; Jonathan R. Ullman (CoRR, 2015)

Private Empirical Risk Minimization: Efficient Algorithms and Tight Error Bounds - Raef Bassily; Adam D. Smith; Abhradeep Thakurta (55th IEEE Annual Symposium on Foundations of Computer Science, FOCS 2014, Philadelphia, PA, USA, October 18-21, 2014, 2014)

Causal Erasure Channels - Raef Bassily; Adam D. Smith (Proceedings of the Twenty-Fifth Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2014, Portland, Oregon, USA, January 5-7, 2014, 2014)

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

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

Cooperative Security at the Physical Layer: A Summary of Recent Advances - Raef Bassily; Ersen Ekrem; Xiang He; 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)

Coupled-Worlds Privacy: Exploiting Adversarial Uncertainty in Statistical Data Privacy - Raef Bassily; Adam Groce; Jonathan Katz; Adam D. Smith (54th Annual IEEE Symposium on Foundations of Computer Science, FOCS 2013, Berkeley, CA, USA, October, 26-29, 2013, 2013)

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)

Deaf cooperation for secrecy with a multi-antenna helper - Raef Bassily; Sennur Ulukus (46th Annual Conference on Information Sciences and Systems, CISS 2012, Princeton, NJ, USA, March 21-23, 2012, 2012)

Decode-and-Forward based strategies for secrecy in multiple-relay networks - Raef Bassily; Sennur Ulukus (2012 IEEE Wireless Communications and Networking Conference, WCNC 2012, Paris, France, April 1-4, 2012, 2012)

Deaf cooperation for secrecy in multiple-relay networks - Raef Bassily; Sennur Ulukus (Workshops Proceedings of the Global Communications Conference, GLOBECOM 2011, 5-9 December 2011, Houston, Texas, USA, 2011)

Ergodic Secret Alignment for the Fading Multiple Access Wiretap Channel - Raef Bassily; Sennur Ulukus (Proceedings of IEEE International Conference on Communications, ICC 2010, Cape Town, South Africa, 23-27 May 2010, 2010)

Ergodic Secret Alignment - Raef Bassily; Sennur Ulukus (CoRR, 2010)

A new achievable ergodic secrecy rate region for the fading multiple access wiretap channel - Raef Bassily; Sennur Ulukus (47th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2009, Monticello, IL, USA, September 30 - October 2, 2009, 2009)