"differential privacy" Papers
72 papers found • Page 1 of 2
A Generalized Binary Tree Mechanism for Private Approximation of All-Pair Shortest Distances
Zongrui Zou, Chenglin Fan, Michael Dinitz et al.
An Iterative Algorithm for Differentially Private $k$-PCA with Adaptive Noise
Johanna Düngler, Amartya Sanyal
Controlling The Spread of Epidemics on Networks with Differential Privacy
Dũng Nguyen, Aravind Srinivasan, Renata Valieva et al.
Differentially Private Bilevel Optimization: Efficient Algorithms with Near-Optimal Rates
Andrew Lowy, Daogao Liu
Differentially Private Federated Low Rank Adaptation Beyond Fixed-Matrix
Ming Wen, Jiaqi Zhu, Yuedong Xu et al.
Differentially private learners for heterogeneous treatment effects
Maresa Schröder, Valentyn Melnychuk, Stefan Feuerriegel
Differential Privacy for Euclidean Jordan Algebra with Applications to Private Symmetric Cone Programming
Zhao Song, Jianfei Xue, Lichen Zhang
DiSK: Differentially Private Optimizer with Simplified Kalman Filter for Noise Reduction
Xinwei Zhang, Zhiqi Bu, Borja Balle et al.
Do You Really Need Public Data? Surrogate Public Data for Differential Privacy on Tabular Data
Shlomi Hod, Lucas Rosenblatt, Julia Stoyanovich
Hot-pluggable Federated Learning: Bridging General and Personalized FL via Dynamic Selection
Lei Shen, Zhenheng Tang, Lijun Wu et al.
Instance-Optimality for Private KL Distribution Estimation
Jiayuan Ye, Vitaly Feldman, Kunal Talwar
Multi-Class Support Vector Machine with Differential Privacy
Jinseong Park, Yujin Choi, Jaewook Lee
Nearly-Linear Time Private Hypothesis Selection with the Optimal Approximation Factor
Maryam Aliakbarpour, Zhan Shi, Ria Stevens et al.
Online robust locally differentially private learning for nonparametric regression
Chenfei Gu, Qiangqiang Zhang, Ting Li et al.
Optimal Best Arm Identification under Differential Privacy
Marc Jourdan, Achraf Azize
Optimal Regret of Bandits under Differential Privacy
Achraf Azize, Yulian Wu, Junya Honda et al.
Privacy-Preserving Personalized Federated Prompt Learning for Multimodal Large Language Models
Linh Tran, Wei Sun, Stacy Patterson et al.
Private Continual Counting of Unbounded Streams
Ben Jacobsen, Kassem Fawaz
Private Mechanism Design via Quantile Estimation
Yuanyuan Yang, Tao Xiao, Bhuvesh Kumar et al.
Private Set Union with Multiple Contributions
Travis Dick, Haim Kaplan, Alex Kulesza et al.
Private Training Large-scale Models with Efficient DP-SGD
Liangyu Wang, Junxiao Wang, Jie Ren et al.
Scaling up the Banded Matrix Factorization Mechanism for Large Scale Differentially Private ML
Ryan McKenna
Sketched Gaussian Mechanism for Private Federated Learning
Qiaobo Li, Zhijie Chen, Arindam Banerjee
Towards hyperparameter-free optimization with differential privacy
Ruixuan Liu, Zhiqi Bu
Unifying Re-Identification, Attribute Inference, and Data Reconstruction Risks in Differential Privacy
Bogdan Kulynych, Juan Gomez, Georgios Kaissis et al.
A New Linear Scaling Rule for Private Adaptive Hyperparameter Optimization
Ashwinee Panda, Xinyu Tang, Saeed Mahloujifar et al.
Auditing Private Prediction
Karan Chadha, Matthew Jagielski, Nicolas Papernot et al.
Beyond the Calibration Point: Mechanism Comparison in Differential Privacy
Georgios Kaissis, Stefan Kolek, Borja de Balle Pigem et al.
CaPS: Collaborative and Private Synthetic Data Generation from Distributed Sources
Sikha Pentyala, Mayana Pereira, Martine De Cock
CuTS: Customizable Tabular Synthetic Data Generation
Mark Vero, Mislav Balunovic, Martin Vechev
Delving into Differentially Private Transformer
Youlong Ding, Xueyang Wu, Yining meng et al.
Differentially Private Bias-Term Fine-tuning of Foundation Models
Zhiqi Bu, Yu-Xiang Wang, Sheng Zha et al.
Differentially Private Decentralized Learning with Random Walks
Edwige Cyffers, Aurélien Bellet, Jalaj Upadhyay
Differentially Private Domain Adaptation with Theoretical Guarantees
Raef Bassily, Corinna Cortes, Anqi Mao et al.
Differentially private exact recovery for stochastic block models
Dung Nguyen, Anil Vullikanti
Differentially Private Post-Processing for Fair Regression
Ruicheng Xian, Qiaobo Li, Gautam Kamath et al.
Differentially Private Representation Learning via Image Captioning
Tom Sander, Yaodong Yu, Maziar Sanjabi et al.
Differentially Private Sum-Product Networks
Xenia Heilmann, Mattia Cerrato, Ernst Althaus
Differentially Private Synthetic Data via Foundation Model APIs 2: Text
Chulin Xie, Zinan Lin, Arturs Backurs et al.
Differentially Private Worst-group Risk Minimization
Xinyu Zhou, Raef Bassily
DP-AdamBC: Your DP-Adam Is Actually DP-SGD (Unless You Apply Bias Correction)
Qiaoyue Tang, Frederick Shpilevskiy, Mathias Lécuyer
FedSC: Provable Federated Self-supervised Learning with Spectral Contrastive Objective over Non-i.i.d. Data
Shusen Jing, Anlan Yu, Shuai Zhang et al.
How Private are DP-SGD Implementations?
Lynn Chua, Badih Ghazi, Pritish Kamath et al.
Improved Communication-Privacy Trade-offs in $L_2$ Mean Estimation under Streaming Differential Privacy
Wei-Ning Chen, Berivan Isik, Peter Kairouz et al.
Individualized Privacy Accounting via Subsampling with Applications in Combinatorial Optimization
Badih Ghazi, Pritish Kamath, Ravi Kumar et al.
Locally Differentially Private Decentralized Stochastic Bilevel Optimization with Guaranteed Convergence Accuracy
Ziqin Chen, Yongqiang Wang
Making Old Things New: A Unified Algorithm for Differentially Private Clustering
Max Dupre la Tour, Monika Henzinger, David Saulpic
Mean Estimation in the Add-Remove Model of Differential Privacy
Alex Kulesza, Ananda Suresh, Yuyan Wang
Nash Incentive-compatible Online Mechanism Learning via Weakly Differentially Private Online Learning
Joon Suk Huh, Kirthevasan Kandasamy
Neural Collapse meets Differential Privacy: Curious behaviors of NoisyGD with Near-Perfect Representation Learning
Chendi Wang, Yuqing Zhu, Weijie Su et al.