Adam Smith - RankMe

29 papers A* 13A 1Journal 15

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Black-Box Privacy Attacks on Shared Representations in Multitask Learning. CoRR John Abascal, Nicolás Berrios, Alina Oprea, Jonathan R. Ullman, Adam Smith, Matthew Jagielski
2025	J	`jnl`	Differentially Private Sampling from Distributions. SIAM J. Comput. Sofya Raskhodnikova, Satchit Sivakumar, Adam Smith, Marika Swanberg
2025	J	`jnl`	Generate-then-Verify: Reconstructing Data from Limited Published Statistics. CoRR Terrance Liu, Eileen Xiao, Pratiksha Thaker, Adam Smith, Zhiwei Steven Wu
2025	J	`jnl`	High-Dimensional Privacy-Utility Dynamics of Noisy Stochastic Gradient Descent on Least Squares. CoRR Shurong Lin, Eric D. Kolaczyk, Adam Smith, Elliot Paquette
2025	A*	`conf`	It's My Data Too: Private ML for Datasets with Multi-User Training Examples. ICML Arun Ganesh, Ryan McKenna, Hugh Brendan McMahan, Adam Smith, Fan Wu
2025	J	`jnl`	It's My Data Too: Private ML for Datasets with Multi-User Training Examples. CoRR Arun Ganesh, Ryan McKenna, Brendan McMahan, Adam Smith, Fan Wu
2025	A	`conf`	Privacy in Metalearning and Multitask Learning: Modeling and Separations. AISTATS Maryam Aliakbarpour, Konstantina Bairaktari, Adam Smith, Marika Swanberg, Jonathan R. Ullman
2025	A*	`conf`	Privately Evaluating Untrusted Black-Box Functions. STOC Ephraim Linder, Sofya Raskhodnikova, Adam Smith, Thomas Steinke
2025	J	`jnl`	Privately Evaluating Untrusted Black-Box Functions. CoRR Ephraim Linder, Sofya Raskhodnikova, Adam Smith, Thomas Steinke
2025	A*	`conf`	The Last Iterate Advantage: Empirical Auditing and Principled Heuristic Analysis of Differentially Private SGD. ICLR Milad Nasr, Thomas Steinke, Borja Balle, Christopher A. Choquette-Choo, Arun Ganesh, Matthew Jagielski, Jamie Hayes, Abhradeep Guha Thakurta, Adam Smith, Andreas Terzis
2024	A*	`conf`	Auditing Privacy Mechanisms via Label Inference Attacks. NeurIPS Róbert Busa-Fekete, Travis Dick, Claudio Gentile, Andrés Muñoz Medina, Adam Smith, Marika Swanberg
2024	J	`jnl`	Auditing Privacy Mechanisms via Label Inference Attacks. CoRR Róbert Istvan Busa-Fekete, Travis Dick, Claudio Gentile, Andrés Muñoz Medina, Adam Smith, Marika Swanberg
2024	A*	`conf`	Insufficient Statistics Perturbation: Stable Estimators for Private Least Squares Extended Abstract. COLT Gavin Brown, Jonathan Hayase, Samuel B. Hopkins, Weihao Kong, Xiyang Liu, Sewoong Oh, Juan C. Perdomo, Adam Smith
2024	J	`jnl`	Insufficient Statistics Perturbation: Stable Estimators for Private Least Squares. CoRR Gavin Brown, Jonathan Hayase, Samuel B. Hopkins, Weihao Kong, Xiyang Liu, Sewoong Oh, Juan C. Perdomo, Adam Smith
2024	A*	`conf`	Metalearning with Very Few Samples Per Task. COLT Maryam Aliakbarpour, Konstantina Bairaktari, Gavin Brown, Adam Smith, Nathan Srebro, Jonathan R. Ullman
2024	A*	`conf`	Optimal Hypothesis Selection in (Almost) Linear Time. NeurIPS Maryam Aliakbarpour, Mark Bun, Adam Smith
2024	A*	`conf`	Private Gradient Descent for Linear Regression: Tighter Error Bounds and Instance-Specific Uncertainty Estimation. ICML Gavin Brown, Krishnamurthy Dj Dvijotham, Georgina Evans, Daogao Liu, Adam Smith, Abhradeep Guha Thakurta
2024	J	`jnl`	Private Gradient Descent for Linear Regression: Tighter Error Bounds and Instance-Specific Uncertainty Estimation. CoRR Gavin Brown, Krishnamurthy Dvijotham, Georgina Evans, Daogao Liu, Adam Smith, Abhradeep Thakurta
2024	J	`jnl`	The Last Iterate Advantage: Empirical Auditing and Principled Heuristic Analysis of Differentially Private SGD. CoRR Thomas Steinke, Milad Nasr, Arun Ganesh, Borja Balle, Christopher A. Choquette-Choo, Matthew Jagielski, Jamie Hayes, Abhradeep Guha Thakurta, Adam Smith, Andreas Terzis
2024	A*	`conf`	Time-Aware Projections: Truly Node-Private Graph Statistics under Continual Observation. SP Palak Jain, Adam Smith, Connor Wagaman
2024	J	`jnl`	Time-Aware Projections: Truly Node-Private Graph Statistics under Continual Observation. CoRR Palak Jain, Adam Smith, Connor Wagaman
2023	A*	`conf`	Counting Distinct Elements in the Turnstile Model with Differential Privacy under Continual Observation. NeurIPS Palak Jain, Iden Kalemaj, Sofya Raskhodnikova, Satchit Sivakumar, Adam Smith
2023	J	`jnl`	Differentially Private Confidence Intervals for Proportions under Stratified Random Sampling. CoRR Shurong Lin, Mark Bun, Marco Gaboardi, Eric D. Kolaczyk, Adam Smith
2023	A*	`conf`	Fast, Sample-Efficient, Affine-Invariant Private Mean and Covariance Estimation for Subgaussian Distributions. COLT Gavin Brown, Samuel B. Hopkins, Adam Smith
2023	A*	`conf`	Hypothesis Selection with Memory Constraints. NeurIPS Maryam Aliakbarpour, Mark Bun, Adam Smith
2023	J	`jnl`	Metalearning with Very Few Samples Per Task. CoRR Maryam Aliakbarpour, Konstantina Bairaktari, Gavin Brown, Adam Smith, Jonathan R. Ullman
2023	A*	`conf`	Triangle Counting with Local Edge Differential Privacy. ICALP Talya Eden, Quanquan C. Liu, Sofya Raskhodnikova, Adam Smith
2022	J	`jnl`	Control, Confidentiality, and the Right to be Forgotten. CoRR Aloni Cohen, Adam Smith, Marika Swanberg, Prashant Nalini Vasudevan
2021	J	`jnl`	The Price of Differential Privacy under Continual Observation. CoRR Palak Jain, Sofya Raskhodnikova, Satchit Sivakumar, Adam Smith