{"total":19,"rows":[{"id":"2201.08430","title":"Reproducibility in Learning","created":"2022-01-20","cited_by_count":44,"area":null},{"id":"2111.04746","title":"Realizable Learning is All You Need","created":"2021-11-08","cited_by_count":25,"area":null},{"id":"2206.03985","title":"How unfair is private learning ?","created":"2022-06-08","cited_by_count":18,"area":null},{"id":"2102.07171","title":"Private learning implies quantum stability","created":"2021-02-14","cited_by_count":10,"area":null},{"id":"2306.03962","title":"PILLAR: How to make semi-private learning more effective","created":"2023-06-06","cited_by_count":10,"area":null},{"id":"2405.15599","title":"On the Computational Landscape of Replicable Learning","created":"2024-05-24","cited_by_count":7,"area":null},{"id":"2406.13433","title":"Certification for Differentially Private Prediction in Gradient-Based Training","created":"2024-06-19","cited_by_count":7,"area":null},{"id":"2407.07765","title":"Ramsey Theorems for Trees and a General 'Private Learning Implies Online Learning' Theorem","created":"2024-07-10","cited_by_count":6,"area":null},{"id":"2304.03996","title":"A Unified Characterization of Private Learnability via Graph Theory","created":"2023-04-08","cited_by_count":5,"area":null},{"id":"2305.09579","title":"Private Everlasting Prediction","created":"2023-05-16","cited_by_count":5,"area":null},{"id":"2402.16778","title":"On the Growth of Mistakes in Differentially Private Online Learning: A Lower Bound Perspective","created":"2024-02-26","cited_by_count":5,"area":null},{"id":"2404.10029","title":"Federated Learning on Riemannian Manifolds with Differential Privacy","created":"2024-04-15","cited_by_count":5,"area":null},{"id":"2105.10594","title":"Privacy Amplification Via Bernoulli Sampling","created":"2021-05-21","cited_by_count":4,"area":null},{"id":"2302.06285","title":"Do PAC-Learners Learn the Marginal Distribution?","created":"2023-02-13","cited_by_count":3,"area":null},{"id":"2510.00076","title":"Private Learning of Littlestone Classes, Revisited","created":"2025-09-30","cited_by_count":3,"area":null},{"id":"2506.12856","title":"Private List Learnability vs. Online List Learnability","created":"2025-06-15","cited_by_count":2,"area":null},{"id":"2201.04762","title":"Privacy Amplification by Subsampling in Time Domain","created":"2022-01-13","cited_by_count":1,"area":null},{"id":"2312.08685","title":"Privacy Amplification by Iteration for ADMM with (Strongly) Convex Objective Functions","created":"2023-12-14","cited_by_count":1,"area":null},{"id":"2506.08347","title":"Differentially Private Relational Learning with Entity-level Privacy Guarantees","created":"2025-06-10","cited_by_count":0,"area":null}],"next_cursor":null}