Showing 1–20 of 73 results
/ Date/ Name
May 1, 2018Privately Learning High-Dimensional DistributionsFeb 21, 2020Private Mean Estimation of Heavy-Tailed DistributionsOct 27, 2021Unbiased Statistical Estimation and Valid Confidence Intervals Under Differential PrivacyOct 13, 2021Differentially Private Fine-tuning of Language ModelsApr 19, 2022Indiscriminate Data Poisoning Attacks on Neural NetworksApr 14, 2023Advancing Differential Privacy: Where We Are Now and Future Directions for Real-World DeploymentDec 4, 2013Faster and Sample Near-Optimal Algorithms for Proper Learning Mixtures of GaussiansNov 11, 2023Report of the 1st Workshop on Generative AI and LawDec 9, 2022Robustness Implies Privacy in Statistical EstimationJul 21, 2015Optimal Testing for Properties of DistributionsNov 17, 2019Random Restrictions of High-Dimensional Distributions and Uniformity Testing with Subcube ConditioningSep 8, 2025Not All Samples Are Equal: Quantifying Instance-level Difficulty in Targeted Data PoisoningAug 16, 2025Demystifying Foreground-Background Memorization in Diffusion ModelsMar 2, 2023Choosing Public Datasets for Private Machine Learning via Gradient Subspace DistanceFeb 21, 2020Privately Learning Markov Random FieldsFeb 27, 2020PAPRIKA: Private Online False Discovery Rate ControlSep 9, 2019Differentially Private Algorithms for Learning Mixtures of Separated GaussiansNov 9, 2021The Role of Adaptive Optimizers for Honest Private Hyperparameter SelectionOct 18, 2020Enabling Fast Differentially Private SGD via Just-in-Time Compilation and VectorizationJan 27, 2022Calibration with Privacy in Peer Review