Showing 1–20 of 46 results
/ Date/ Name
Jul 2, 2021Asymptotic Statistical Analysis of Sparse Group LASSO via Approximate Message Passing AlgorithmMay 21, 2022Scalable and Efficient Training of Large Convolutional Neural Networks with Differential PrivacyNov 20, 2023Zero redundancy distributed learning with differential privacyOct 30, 2023On the accuracy and efficiency of group-wise clipping in differentially private optimizationJul 12, 2025Sharp Trade-Offs in High-Dimensional Inference via 2-Level SLOPEFeb 6, 2026Convex Dominance in Deep Learning I: A Scaling Law of Loss and Learning RateOct 2, 2023Coupling public and private gradient provably helps optimizationJun 14, 2022Automatic Clipping: Differentially Private Deep Learning Made Easier and StrongerMay 27, 2021Characterizing the SLOPE Trade-off: A Variational Perspective and the Donoho-Tanner LimitFeb 14, 2021Efficient Designs of SLOPE Penalty Sequences in Finite DimensionJun 17, 2021Accuracy, Interpretability, and Differential Privacy via Explainable BoostingAug 24, 2024DOPPLER: Differentially Private Optimizers with Low-pass Filter for Privacy Noise ReductionOct 29, 2024Unlearning as multi-task optimization: A normalized gradient difference approach with an adaptive learning rateJul 21, 2020The Complete Lasso Tradeoff DiagramNov 16, 2022Differentially Private Optimizers Can Learn Adversarially Robust ModelsSep 30, 2022Differentially Private Optimization on Large Model at Small CostSep 30, 2022Differentially Private Bias-Term Fine-tuning of Foundation ModelsFeb 28, 2024Pre-training Differentially Private Models with Limited Public DataMar 2, 2025Towards hyperparameter-free optimization with differential privacyOct 4, 2024DiSK: Differentially Private Optimizer with Simplified Kalman Filter for Noise Reduction