Raef Bassily - RankMe

84 papers A* 26A 4B 5C 1Misc 1Journal 41Unranked 6

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Data Sharing with Endogenous Choices over Differential Privacy Levels. CoRR Raef Bassily, Kate Donahue, Diptangshu Sen, Annuo Zhao, Juba Ziani
2025	A*	`conf`	Private Model Personalization Revisited. ICML Conor Snedeker, Xinyu Zhou, Raef Bassily
2025	J	`jnl`	Private Model Personalization Revisited. CoRR Conor Snedeker, Xinyu Zhou, Raef Bassily
2024	A*	`conf`	Differentially Private Domain Adaptation with Theoretical Guarantees. ICML Raef Bassily, Corinna Cortes, Anqi Mao, Mehryar Mohri
2024	B	`conf`	Differentially Private Non-Convex Optimization under the KL Condition with Optimal Rates. ALT Michael Menart, Enayat Ullah, Raman Arora, Raef Bassily, Cristóbal Guzmán
2024	A*	`conf`	Differentially Private Worst-group Risk Minimization. ICML Xinyu Zhou, Raef Bassily
2024	J	`jnl`	Differentially Private Worst-group Risk Minimization. CoRR Xinyu Zhou, Raef Bassily
2024	A*	`conf`	Private Algorithms for Stochastic Saddle Points and Variational Inequalities: Beyond Euclidean Geometry. NeurIPS Raef Bassily, Cristóbal Guzmán, Michael Menart
2024	J	`jnl`	Private Algorithms for Stochastic Saddle Points and Variational Inequalities: Beyond Euclidean Geometry. CoRR Raef Bassily, Cristóbal Guzmán, Michael Menart
2024	A*	`conf`	Public-data Assisted Private Stochastic Optimization: Power and Limitations. NeurIPS Enayat Ullah, Michael Menart, Raef Bassily, Cristóbal Guzmán, Raman Arora
2024	J	`jnl`	Public-data Assisted Private Stochastic Optimization: Power and Limitations. CoRR Enayat Ullah, Michael Menart, Raef Bassily, Cristóbal Guzmán, Raman Arora
2023	A*	`conf`	Differentially Private Algorithms for the Stochastic Saddle Point Problem with Optimal Rates for the Strong Gap. COLT Raef Bassily, Cristóbal Guzmán, Michael Menart
2023	J	`jnl`	Differentially Private Algorithms for the Stochastic Saddle Point Problem with Optimal Rates for the Strong Gap. CoRR Raef Bassily, Cristóbal Guzmán, Michael Menart
2023	J	`jnl`	Differentially Private Domain Adaptation with Theoretical Guarantees. CoRR Raef Bassily, Corinna Cortes, Anqi Mao, Mehryar Mohri
2023	J	`jnl`	Differentially Private Non-Convex Optimization under the KL Condition with Optimal Rates. CoRR Michael Menart, Enayat Ullah, Raman Arora, Raef Bassily, Cristóbal Guzmán
2023	A*	`conf`	Faster Rates of Convergence to Stationary Points in Differentially Private Optimization. ICML Raman Arora, Raef Bassily, Tomás González, Cristóbal Guzmán, Michael Menart, Enayat Ullah
2023	A	`conf`	Principled Approaches for Private Adaptation from a Public Source. AISTATS Raef Bassily, Mehryar Mohri, Ananda Theertha Suresh
2023	A*	`conf`	User-level Private Stochastic Convex Optimization with Optimal Rates. ICML Raef Bassily, Ziteng Sun
2022	A*	`conf`	Differentially Private Generalized Linear Models Revisited. NeurIPS Raman Arora, Raef Bassily, Cristóbal Guzmán, Michael Menart, Enayat Ullah
2022	J	`jnl`	Differentially Private Generalized Linear Models Revisited. CoRR Raman Arora, Raef Bassily, Cristóbal Guzmán, Michael Menart, Enayat Ullah
2022	A*	`conf`	Differentially Private Learning with Margin Guarantees. NeurIPS Raef Bassily, Mehryar Mohri, Ananda Theertha Suresh
2022	J	`jnl`	Differentially Private Learning with Margin Guarantees. CoRR Raef Bassily, Mehryar Mohri, Ananda Theertha Suresh
2022	J	`jnl`	Faster Rates of Convergence to Stationary Points in Differentially Private Optimization. CoRR Raman Arora, Raef Bassily, Tomás González, Cristóbal Guzmán, Michael Menart, Enayat Ullah
2022	—	`conf`	Leveraging Synergies Between AI and Networking to Build Next Generation Edge Networks. CIC 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, Jim Kurose, Yingbin Liang, Zhiqiang Lin, Jia Liu, Mingyan Liu, Tommaso Melodia, Aryan Mokhtari, Rob Nowak, Sewoong Oh, Srini Parthasarathy, Chunyi Peng, Hulya Seferoglu, Ness B. Shroff, Sanjay Shakkottai, Kannan Srinivasan, Ameet Talwalkar, Aylin Yener, Lei Ying
2022	J	`jnl`	Private Domain Adaptation from a Public Source. CoRR Raef Bassily, Mehryar Mohri, Ananda Theertha Suresh
2022	A*	`conf`	Task-level Differentially Private Meta Learning. NeurIPS Xinyu Zhou, Raef Bassily
2021	J	`jnl`	Algorithmic Stability for Adaptive Data Analysis. SIAM J. Comput. Raef Bassily, Kobbi Nissim, Adam D. Smith, Thomas Steinke, Uri Stemmer, Jonathan R. Ullman
2021	J	`jnl`	Differential Privacy for Coverage Analysis of Software Traces (Artifact). Dagstuhl Artifacts Ser. Yu Hao, Sufian Latif, Hailong Zhang, Raef Bassily, Atanas Rountev
2021	A	`conf`	Differential Privacy for Coverage Analysis of Software Traces. ECOOP Yu Hao, Sufian Latif, Hailong Zhang, Raef Bassily, Atanas Rountev
2021	A*	`conf`	Differentially Private Stochastic Optimization: New Results in Convex and Non-Convex Settings. NeurIPS Raef Bassily, Cristóbal Guzmán, Michael Menart
2021	J	`jnl`	Differentially Private Stochastic Optimization: New Results in Convex and Non-Convex Settings. CoRR Raef Bassily, Cristóbal Guzmán, Michael Menart
2021	A*	`conf`	Non-Euclidean Differentially Private Stochastic Convex Optimization. COLT Raef Bassily, Cristóbal Guzmán, Anupama Nandi
2021	J	`jnl`	Non-Euclidean Differentially Private Stochastic Convex Optimization. CoRR Raef Bassily, Cristóbal Guzmán, Anupama Nandi
2020	B	`conf`	A study of event frequency profiling with differential privacy. CC Hailong Zhang, Yu Hao, Sufian Latif, Raef Bassily, Atanas Rountev
2020	A*	`conf`	Differentially-Private Control-Flow Node Coverage for Software Usage Analysis. USENIX Security Symposium Hailong Zhang, Sufian Latif, Raef Bassily, Atanas Rountev
2020	J	`jnl`	Differentially-private software frequency profiling under linear constraints. Proc. ACM Program. Lang. Hailong Zhang, Yu Hao, Sufian Latif, Raef Bassily, Atanas Rountev
2020	A	`conf`	Introducing Differential Privacy Mechanisms for Mobile App Analytics of Dynamic Content. ICSME Sufian Latif, Yu Hao, Hailong Zhang, Raef Bassily, Atanas Rountev
2020	A*	`conf`	Learning from Mixtures of Private and Public Populations. NeurIPS Raef Bassily, Shay Moran, Anupama Nandi
2020	J	`jnl`	Learning from Mixtures of Private and Public Populations. CoRR Raef Bassily, Shay Moran, Anupama Nandi
2020	J	`jnl`	Practical Locally Private Heavy Hitters. J. Mach. Learn. Res. Raef Bassily, Kobbi Nissim, Uri Stemmer, Abhradeep Thakurta
2020	A*	`conf`	Private Query Release Assisted by Public Data. ICML Raef Bassily, Albert Cheu, Shay Moran, Aleksandar Nikolov, Jonathan R. Ullman, Zhiwei Steven Wu
2020	J	`jnl`	Private Query Release Assisted by Public Data. CoRR Raef Bassily, Albert Cheu, Shay Moran, Aleksandar Nikolov, Jonathan R. Ullman, Zhiwei Steven Wu
2020	B	`conf`	Privately Answering Classification Queries in the Agnostic PAC Model. ALT Anupama Nandi, Raef Bassily
2020	A*	`conf`	Stability of Stochastic Gradient Descent on Nonsmooth Convex Losses. NeurIPS Raef Bassily, Vitaly Feldman, Cristóbal Guzmán, Kunal Talwar
2020	J	`jnl`	Stability of Stochastic Gradient Descent on Nonsmooth Convex Losses. CoRR Raef Bassily, Vitaly Feldman, Cristóbal Guzmán, Kunal Talwar
2019	C	`conf`	Introducing Privacy in Screen Event Frequency Analysis for Android Apps. SCAM Hailong Zhang, Sufian Latif, Raef Bassily, Atanas Rountev
2019	A*	`conf`	Limits of Private Learning with Access to Public Data. NeurIPS Raef Bassily, Shay Moran, Noga Alon
2019	J	`jnl`	Limits of Private Learning with Access to Public Data. CoRR Noga Alon, Raef Bassily, Shay Moran
2019	A	`conf`	Linear Queries Estimation with Local Differential Privacy. AISTATS Raef Bassily
2019	A*	`conf`	Private Stochastic Convex Optimization with Optimal Rates. NeurIPS Raef Bassily, Vitaly Feldman, Kunal Talwar, Abhradeep Guha Thakurta
2019	J	`jnl`	Private Stochastic Convex Optimization with Optimal Rates. CoRR Raef Bassily, Vitaly Feldman, Kunal Talwar, Abhradeep Thakurta
2019	J	`jnl`	Privately Answering Classification Queries in the Agnostic PAC Model. CoRR Raef Bassily, Anupama Nandi
2018	—	`conf`	Differentially-private software analytics for mobile apps: opportunities and challenges. SWAN@ESEC/SIGSOFT FSE Hailong Zhang, Sufian Latif, Raef Bassily, Atanas Rountev
2018	B	`conf`	Learners that Use Little Information. ALT Raef Bassily, Shay Moran, Ido Nachum, Jonathan Shafer, Amir Yehudayoff
2018	J	`jnl`	Linear Queries Estimation with Local Differential Privacy. CoRR Raef Bassily
2018	J	`jnl`	Model-Agnostic Private Learning via Stability. CoRR Raef Bassily, Om Thakkar, Abhradeep Thakurta
2018	A*	`conf`	Model-Agnostic Private Learning. NeurIPS Raef Bassily, Abhradeep Guha Thakurta, Om Dipakbhai Thakkar
2018	J	`jnl`	On exponential convergence of SGD in non-convex over-parametrized learning. CoRR Raef Bassily, Mikhail Belkin, Siyuan Ma
2018	A*	`conf`	The Power of Interpolation: Understanding the Effectiveness of SGD in Modern Over-parametrized Learning. ICML Siyuan Ma, Raef Bassily, Mikhail Belkin
2017	J	`jnl`	Learners that Leak Little Information. CoRR Raef Bassily, Shay Moran, Ido Nachum, Jonathan Shafer, Amir Yehudayoff
2017	—	`conf`	Practical Locally Private Heavy Hitters. NIPS Raef Bassily, Kobbi Nissim, Uri Stemmer, Abhradeep Guha Thakurta
2017	J	`jnl`	Practical Locally Private Heavy Hitters. CoRR Raef Bassily, Kobbi Nissim, Uri Stemmer, Abhradeep Thakurta
2017	J	`jnl`	The Power of Interpolation: Understanding the Effectiveness of SGD in Modern Over-parametrized Learning. CoRR Siyuan Ma, Raef Bassily, Mikhail Belkin
2016	A*	`conf`	Algorithmic stability for adaptive data analysis. STOC Raef Bassily, Kobbi Nissim, Adam D. Smith, Thomas Steinke, Uri Stemmer, Jonathan R. Ullman
2016	J	`jnl`	Typicality-Based Stability and Privacy. CoRR Raef Bassily, Yoav Freund
2015	J	`jnl`	Algorithmic Stability for Adaptive Data Analysis. CoRR Raef Bassily, Kobbi Nissim, Adam D. Smith, Thomas Steinke, Uri Stemmer, Jonathan R. Ullman
2015	A*	`conf`	Local, Private, Efficient Protocols for Succinct Histograms. STOC Raef Bassily, Adam D. Smith
2015	J	`jnl`	Local, Private, Efficient Protocols for Succinct Histograms. CoRR Raef Bassily, Adam D. Smith
2014	A*	`conf`	Causal Erasure Channels. SODA Raef Bassily, Adam D. Smith
2014	J	`jnl`	Causal Erasure Channels. CoRR Raef Bassily, Adam D. Smith
2014	J	`jnl`	Private Empirical Risk Minimization, Revisited. CoRR Raef Bassily, Adam D. Smith, Abhradeep Thakurta
2014	A*	`conf`	Private Empirical Risk Minimization: Efficient Algorithms and Tight Error Bounds. FOCS Raef Bassily, Adam D. Smith, Abhradeep Thakurta
2013	J	`jnl`	Cooperative Security at the Physical Layer: A Summary of Recent Advances. IEEE Signal Process. Mag. Raef Bassily, Ersen Ekrem, Xiang He, Ender Tekin, Jianwei Xie, Matthieu R. Bloch, Sennur Ulukus, Aylin Yener
2013	A*	`conf`	Coupled-Worlds Privacy: Exploiting Adversarial Uncertainty in Statistical Data Privacy. FOCS Raef Bassily, Adam Groce, Jonathan Katz, Adam D. Smith
2013	J	`jnl`	Deaf Cooperation and Relay Selection Strategies for Secure Communication in Multiple Relay Networks. IEEE Trans. Signal Process. Raef Bassily, Sennur Ulukus
2012	J	`jnl`	Deaf Cooperation for Secrecy With Multiple Antennas at the Helper. IEEE Trans. Inf. Forensics Secur. Raef Bassily, Sennur Ulukus
2012	Misc	`conf`	Deaf cooperation for secrecy with a multi-antenna helper. CISS Raef Bassily, Sennur Ulukus
2012	B	`conf`	Decode-and-Forward based strategies for secrecy in multiple-relay networks. WCNC Raef Bassily, Sennur Ulukus
2012	J	`jnl`	Ergodic Secret Alignment. IEEE Trans. Inf. Theory Raef Bassily, Sennur Ulukus
2012	J	`jnl`	Secure communication in multiple relay networks through decode-and-forward strategies. J. Commun. Networks Raef Bassily, Sennur Ulukus
2011	—	`conf`	Deaf cooperation for secrecy in multiple-relay networks. GLOBECOM Workshops Raef Bassily, Sennur Ulukus
2010	J	`jnl`	Ergodic Secret Alignment CoRR Raef Bassily, Sennur Ulukus
2010	—	`conf`	Ergodic Secret Alignment for the Fading Multiple Access Wiretap Channel. ICC Raef Bassily, Sennur Ulukus
2009	—	`conf`	A new achievable ergodic secrecy rate region for the fading multiple access wiretap channel. Allerton Raef Bassily, Sennur Ulukus

Nicolò Altamura is a security engineer and computer science researcher specializing in software protection, reverse engineering, program analysis, and binary deobfuscation. He holds a master's degree in Computer Science and Engineering from the University of Verona, graduating with honors, and works at emproof, focusing on software protection and the challenges of analyzing and understanding compiled software.

His research explores the relationship between program analysis and code obfuscation, with particular emphasis on how software transformations affect the ability of automated tools to recover program behavior. His interests span static analysis, binary analysis, decompilation, reverse engineering, and techniques for analyzing and simplifying obfuscated code.

Beyond academic research, Nicolò develops and contributes to tools for reverse engineering and software analysis. His projects include obfuscation_analysis, a Binary Ninja plugin for analyzing and simplifying obfuscated code; Pocket, an obfuscator for mixed Boolean-arithmetic expressions; and ptxNinja, a tool for reverse engineering NVIDIA GPU code represented in the PTX virtual instruction set.

His research also extends to binary datasets and software evolution. In 2026, he co-authored ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage, a research work addressing the availability of binary data across multiple software builds and points in time, supporting research into binary analysis and changes between program versions.

Across his research, engineering work, and open-source contributions, Nicolò focuses on advancing the understanding, analysis, and protection of software against increasingly sophisticated obfuscation and reverse-engineering challenges.

Nicolò Altamura is not a football player. Please avoid reporting this kind of infromation.