v1v2 (latest)

High Dimensional Differentially Private Stochastic Optimization with Heavy-tailed Data

23 July 2021

Lijie Hu

Papers citing "High Dimensional Differentially Private Stochastic Optimization with Heavy-tailed Data"

36 / 36 papers shown

Title
Differentially Private Sparse Linear Regression with Heavy-tailed Responses Xizhi Tian Meng Ding Touming Tao Zihang Xiang Di Wang 18 0 0 07 Jun 2025
Second-Order Convergence in Private Stochastic Non-Convex Optimization Youming Tao Zuyuan Zhang Dongxiao Yu Xiuzhen Cheng Falko Dressler Di Wang 59 1 0 21 May 2025
Towards User-level Private Reinforcement Learning with Human Feedback Jing Zhang Mingxi Lei Meng Ding Mengdi Li Zihang Xiang Difei Xu Jinhui Xu Di Wang 107 3 0 22 Feb 2025
Private Language Models via Truncated Laplacian Mechanism Tianhao Huang Tao Yang Ivan Habernal Lijie Hu Di Wang 54 1 0 10 Oct 2024
Differential Private Stochastic Optimization with Heavy-tailed Data: Towards Optimal Rates Puning Zhao Xiaogang Xu Zhe Liu Chong Wang Rongfei Fan Qingming Li 72 1 0 19 Aug 2024
Better Locally Private Sparse Estimation Given Multiple Samples Per User Yuheng Ma Ke Jia Hanfang Yang FedML 85 1 0 08 Aug 2024
Delving into Differentially Private Transformer Youlong Ding Xueyang Wu Yining Meng Yonggang Luo Hao Wang Weike Pan 123 5 0 28 May 2024
Leveraging Logical Rules in Knowledge Editing: A Cherry on the Top Keyuan Cheng Muhammad Asif Ali Shu Yang Gang Lin Yuxuan Zhai Haoyang Fei Ke Xu Lu Yu Lijie Hu Di Wang KELM 117 11 0 24 May 2024
SoK: A Review of Differentially Private Linear Models For High-Dimensional Data Amol Khanna Edward Raff Nathan Inkawhich 72 4 0 01 Apr 2024
Multi-hop Question Answering under Temporal Knowledge Editing Keyuan Cheng Gang Lin Haoyang Fei Yuxuan Zhai Lu Yu Muhammad Asif Ali Lijie Hu Di Wang KELM 100 27 0 30 Mar 2024
PROMPT-SAW: Leveraging Relation-Aware Graphs for Textual Prompt Compression Muhammad Asif Ali Zhengping Li Shu Yang Keyuan Cheng Yang Cao Tianhao Huang Lijie Hu Lu Yu Di Wang VLM RALM 83 9 0 30 Mar 2024
Dialectical Alignment: Resolving the Tension of 3H and Security Threats of LLMs Shu Yang Jiayuan Su Han Jiang Mengdi Li Keyuan Cheng Muhammad Asif Ali Lijie Hu Di Wang 95 6 0 30 Mar 2024
SPriFed-OMP: A Differentially Private Federated Learning Algorithm for Sparse Basis Recovery Ajinkya Kiran Mulay Xiaojun Lin 49 0 0 29 Feb 2024
MONAL: Model Autophagy Analysis for Modeling Human-AI Interactions Shu Yang Muhammad Asif Ali Lu Yu Lijie Hu Di Wang LLMAG 72 5 0 17 Feb 2024
Efficient Sparse Least Absolute Deviation Regression with Differential Privacy Weidong Liu Xiaojun Mao Xiaofei Zhang Xin Zhang 55 2 0 02 Jan 2024
Scaling Up Differentially Private LASSO Regularized Logistic Regression via Faster Frank-Wolfe Iterations Edward Raff Amol Khanna Fred Lu 60 7 0 30 Oct 2023
Differentially Private Non-convex Learning for Multi-layer Neural Networks Hanpu Shen Cheng-Long Wang Zihang Xiang Yiming Ying Di Wang 81 8 0 12 Oct 2023
Improved Analysis of Sparse Linear Regression in Local Differential Privacy Model Liyang Zhu Meng Ding Vaneet Aggarwal Jinhui Xu Di Wang 40 5 0 11 Oct 2023
Geometry of Sensitivity: Twice Sampling and Hybrid Clipping in Differential Privacy with Optimal Gaussian Noise and Application to Deep Learning Hanshen Xiao Jun Wan Srini Devadas 33 8 0 06 Sep 2023
Differentially Private Episodic Reinforcement Learning with Heavy-tailed Rewards Yulian Wu Xingyu Zhou Sayak Ray Chowdhury Di Wang 60 2 0 01 Jun 2023
DPFormer: Learning Differentially Private Transformer on Long-Tailed Data Youlong Ding Xueyang Wu Hongya Wang Weike Pan 95 1 0 28 May 2023
Differentially Private Stochastic Convex Optimization in (Non)-Euclidean Space Revisited Jinyan Su Changhong Zhao Di Wang 60 5 0 31 Mar 2023
Byzantine-Resilient Federated Learning at Edge Youming Tao Sijia Cui Wenlu Xu Haofei Yin Dongxiao Yu W. Liang Xiuzhen Cheng FedML 48 19 0 18 Mar 2023
DIFF2: Differential Private Optimization via Gradient Differences for Nonconvex Distributed Learning Tomoya Murata Taiji Suzuki 83 9 0 08 Feb 2023
Differentially Private Natural Language Models: Recent Advances and Future Directions Lijie Hu Ivan Habernal Lei Shen Di Wang AAML 87 19 0 22 Jan 2023
Differentially Private Deep Learning with ModelMix Hanshen Xiao Jun Wan S. Devadas 70 3 0 07 Oct 2022
Truthful Generalized Linear Models Yuan Qiu Jinyan Liu Di Wang FedML 78 2 0 16 Sep 2022
Private Stochastic Optimization With Large Worst-Case Lipschitz Parameter: Optimal Rates for (Non-Smooth) Convex Losses and Extension to Non-Convex Losses Andrew Lowy Meisam Razaviyayn 86 13 0 15 Sep 2022
High-Dimensional Private Empirical Risk Minimization by Greedy Coordinate Descent Paul Mangold A. Bellet Joseph Salmon Marc Tommasi 68 5 0 04 Jul 2022
Efficient Private SCO for Heavy-Tailed Data via Clipping Chenhan Jin Kaiwen Zhou Bo Han Ming Yang James Cheng 37 1 0 27 Jun 2022
Beyond Uniform Lipschitz Condition in Differentially Private Optimization Rudrajit Das Satyen Kale Zheng Xu Tong Zhang Sujay Sanghavi 94 19 0 21 Jun 2022
$On Private Online Convex Optimization: Optimal Algorithms in $\ell_p$-Geometry and High Dimensional Contextual Bandits$ On Private Online Convex Optimization: Optimal Algorithms in $\ell_p$ -Geometry and High Dimensional Contextual Bandits Yuxuan Han Zhicong Liang Zhipeng Liang Yang Wang Yuan Yao Jiheng Zhang 58 1 0 16 Jun 2022
DP-PCA: Statistically Optimal and Differentially Private PCA Xiyang Liu Weihao Kong Prateek Jain Sewoong Oh 127 24 0 27 May 2022
High Dimensional Statistical Estimation under Uniformly Dithered One-bit Quantization Junren Chen Cheng-Long Wang Michael Kwok-Po Ng Di Wang MQ 98 20 0 26 Feb 2022
$Differentially Private $\ell_1$-norm Linear Regression with Heavy-tailed Data$ Differentially Private $\ell_1$ -norm Linear Regression with Heavy-tailed Data Di Wang Jinhui Xu 42 7 0 10 Jan 2022
Estimating Smooth GLM in Non-interactive Local Differential Privacy Model with Public Unlabeled Data Di Wang Lijie Hu Huanyu Zhang Marco Gaboardi Jinhui Xu 127 9 0 01 Oct 2019