Zakynthinou, Lydia

12 publications

ICML 2025 Empirical Privacy Variance Yuzheng Hu, Fan Wu, Ruicheng Xian, Yuhang Liu, Lydia Zakynthinou, Pritish Kamath, Chiyuan Zhang, David Forsyth

NeurIPS 2024 Dimension-Free Private Mean Estimation for Anisotropic Distributions Yuval Dagan, Michael I. Jordan, Xuelin Yang, Lydia Zakynthinou, Nikita Zhivotovskiy

ICML 2023 From Robustness to Privacy and Back Hilal Asi, Jonathan Ullman, Lydia Zakynthinou

COLT 2023 Multitask Learning via Shared Features: Algorithms and Hardness Konstantina Bairaktari, Guy Blanc, Li-Yang Tan, Jonathan Ullman, Lydia Zakynthinou

NeurIPS 2021 Covariance-Aware Private Mean Estimation Without Private Covariance Estimation Gavin Brown, Marco Gaboardi, Adam Smith, Jonathan Ullman, Lydia Zakynthinou

AAAI 2021 Differentially Private Decomposable Submodular Maximization Anamay Chaturvedi, Huy Le Nguyen, Lydia Zakynthinou

COLT 2021 PAC-Bayes, MAC-Bayes and Conditional Mutual Information: Fast Rate Bounds That Handle General VC Classes Peter Grunwald, Thomas Steinke, Lydia Zakynthinou

ALT 2020 Efficient Private Algorithms for Learning Large-Margin Halfspaces Huy Lê Nguyễn, Jonathan Ullman, Lydia Zakynthinou

COLT 2020 Open Problem: Information Complexity of VC Learning Thomas Steinke, Lydia Zakynthinou

NeurIPS 2020 Private Identity Testing for High-Dimensional Distributions Clément L Canonne, Gautam Kamath, Audra McMillan, Jonathan Ullman, Lydia Zakynthinou

COLT 2020 Reasoning About Generalization via Conditional Mutual Information Thomas Steinke, Lydia Zakynthinou

NeurIPS 2018 Improved Algorithms for Collaborative PAC Learning Huy Nguyen, Lydia Zakynthinou