{"total":20,"rows":[{"id":"2302.04787","title":"On the Privacy-Robustness-Utility Trilemma in Distributed Learning","created":"2023-02-09","cited_by_count":24,"area":null},{"id":"2202.10209","title":"Degree-Preserving Randomized Response for Graph Neural Networks under Local Differential Privacy","created":"2022-02-21","cited_by_count":9,"area":null},{"id":"2505.01874","title":"Towards Trustworthy Federated Learning with Untrusted Participants","created":"2025-05-03","cited_by_count":8,"area":null},{"id":"2110.15444","title":"10 Security and Privacy Problems in Large Foundation Models","created":"2021-10-28","cited_by_count":6,"area":null},{"id":"2307.15017","title":"Samplable Anonymous Aggregation for Private Federated Data Analysis","created":"2023-07-27","cited_by_count":6,"area":null},{"id":"2104.10740","title":"Robust Testing and Estimation under Manipulation Attacks","created":"2021-04-21","cited_by_count":5,"area":null},{"id":"2202.06825","title":"Robust Estimation of Discrete Distributions under Local Differential Privacy","created":"2022-02-14","cited_by_count":5,"area":null},{"id":"2202.10618","title":"Differential Secrecy for Distributed Data and Applications to Robust Differentially Secure Vector Summation","created":"2022-02-22","cited_by_count":5,"area":null},{"id":"2205.09986","title":"SafeNet: The Unreasonable Effectiveness of Ensembles in Private Collaborative Learning","created":"2022-05-20","cited_by_count":5,"area":null},{"id":"2404.10201","title":"Private Vector Mean Estimation in the Shuffle Model: Optimal Rates Require Many Messages","created":"2024-04-16","cited_by_count":5,"area":null},{"id":"2110.11578","title":"PRECAD: Privacy-Preserving and Robust Federated Learning via Crypto-Aided Differential Privacy","created":"2021-10-22","cited_by_count":3,"area":null},{"id":"2309.11691","title":"RAI4IoE: Responsible AI for Enabling the Internet of Energy","created":"2023-09-20","cited_by_count":3,"area":null},{"id":"2307.00268","title":"Hiding in Plain Sight: Differential Privacy Noise Exploitation for Evasion-resilient Localized Poisoning Attacks in Multiagent Reinforcement Learning","created":"2023-07-01","cited_by_count":2,"area":null},{"id":"2312.14712","title":"Balancing Privacy, Robustness, and Efficiency in Machine Learning","created":"2023-12-22","cited_by_count":1,"area":null},{"id":"2501.18803","title":"Deceptive Sequential Decision-Making via Regularized Policy Optimization","created":"2025-01-30","cited_by_count":1,"area":null},{"id":"2503.07483","title":"Poisoning Attacks to Local Differential Privacy Protocols for Trajectory Data","created":"2025-03-06","cited_by_count":1,"area":null},{"id":"2103.09927","title":"Encrypted Linear Contextual Bandit","created":"2021-03-17","cited_by_count":0,"area":null},{"id":"2402.16157","title":"Consensus learning: A novel decentralised ensemble learning paradigm","created":"2024-02-25","cited_by_count":0,"area":null},{"id":"2604.17476","title":"Privatar: Scalable Privacy-preserving Multi-user VR via Secure Offloading","created":"2026-04-19","cited_by_count":0,"area":null},{"id":"2607.27815","title":"Robust Estimation of Sparse Numerical Vectors under Local Differential Privacy","created":"2026-07-30","cited_by_count":0,"area":null}],"next_cursor":null}