:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Gao, Yeqi, Song, Zhao, Yang, Xin, Zhou, Yufa
Format:	Preprint
Published:	2023
Subjects:	Machine Learning Cryptography and Security
Online Access:	https://arxiv.org/abs/2305.04701
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Provable Differentially Private Computation of the Cross-Attention Mechanism
by: Ke, Yekun, et al.
Published: (2024)

Beyond Statistical Estimation: Differentially Private Individual Computation via Shuffling
by: Wang, Shaowei, et al.
Published: (2024)

Training Differentially Private Models with Secure Multiparty Computation
by: Pentyala, Sikha, et al.
Published: (2022)

Data-adaptive Differentially Private Prompt Synthesis for In-Context Learning
by: Gao, Fengyu, et al.
Published: (2024)

Private Linear Regression with Differential Privacy and PAC Privacy
by: Yang, Hillary, et al.
Published: (2024)

Differentially Private Preference Data Synthesis for Large Language Model Alignment
by: Gao, Fengyu, et al.
Published: (2026)

Delving into Differentially Private Transformer
by: Ding, Youlong, et al.
Published: (2024)

Differentially Private Diffusion Models
by: Dockhorn, Tim, et al.
Published: (2022)

Privately Learning Decision Lists and a Differentially Private Winnow
by: Bun, Mark, et al.
Published: (2026)

Differentially Private Low-Rank Adaptation of Large Language Model Using Federated Learning
by: Liu, Xiao-Yang, et al.
Published: (2023)

Differentially Private Range Queries with Correlated Input Perturbation
by: Dharangutte, Prathamesh, et al.
Published: (2024)

Private and Communication-Efficient Federated Learning based on Differentially Private Sketches
by: Zhang, Meifan, et al.
Published: (2024)

Entropy-Guided Attention for Private LLMs
by: Jha, Nandan Kumar, et al.
Published: (2025)

DPIS: An Enhanced Mechanism for Differentially Private SGD with Importance Sampling
by: Wei, Jianxin, et al.
Published: (2022)

Differentially Private Conditional Independence Testing
by: Kalemaj, Iden, et al.
Published: (2023)

Differentially Private Random Feature Model
by: Liao, Chunyang, et al.
Published: (2024)

Differentially Private Federated Learning: A Systematic Review
by: Fu, Jie, et al.
Published: (2024)

Differentially Private Subspace Fine-Tuning for Large Language Models
by: Zheng, Lele, et al.
Published: (2026)

AdaPI: Facilitating DNN Model Adaptivity for Efficient Private Inference in Edge Computing
by: Zhou, Tong, et al.
Published: (2024)

Privacy-Preserving Federated Learning with Differentially Private Hyperdimensional Computing
by: Piran, Fardin Jalil, et al.
Published: (2024)

Differentially Private Worst-group Risk Minimization
by: Zhou, Xinyu, et al.
Published: (2024)

Differentially Private Domain Adaptation with Theoretical Guarantees
by: Bassily, Raef, et al.
Published: (2023)

Practical Differentially Private Hyperparameter Tuning with Subsampling
by: Koskela, Antti, et al.
Published: (2023)

Scaling Laws for Differentially Private Language Models
by: McKenna, Ryan, et al.
Published: (2025)

Differentially Private Learners for Heterogeneous Treatment Effects
by: Schröder, Maresa, et al.
Published: (2025)

Differentially Private Training of Mixture of Experts Models
by: Tholoniat, Pierre, et al.
Published: (2024)

Revisiting Differentially Private Hyper-parameter Tuning
by: Xiang, Zihang, et al.
Published: (2024)

Correlated Noise Mechanisms for Differentially Private Learning
by: Pillutla, Krishna, et al.
Published: (2025)

Differentially Private Release and Learning of Threshold Functions
by: Bun, Mark, et al.
Published: (2015)

Differentially Private Decentralized Learning with Random Walks
by: Cyffers, Edwige, et al.
Published: (2024)

Noise-Aware Differentially Private Variational Inference
by: Alrawajfeh, Talal, et al.
Published: (2024)

Mitigating Noise Detriment in Differentially Private Federated Learning with Model Pre-training
by: Jin, Huitong, et al.
Published: (2024)

Audit to Forget: A Unified Method to Revoke Patients' Private Data in Intelligent Healthcare
by: Zhou, Juexiao, et al.
Published: (2023)

Differentially Private E-Values
by: Csillag, Daniel, et al.
Published: (2025)

Differentially Private Learned Indexes
by: Du, Jianzhang, et al.
Published: (2024)

ACTG-ARL: Differentially Private Conditional Text Generation with RL-Boosted Control
by: Hu, Yuzheng, et al.
Published: (2025)

S-BDT: Distributed Differentially Private Boosted Decision Trees
by: Peinemann, Thorsten, et al.
Published: (2023)

DP-LDMs: Differentially Private Latent Diffusion Models
by: Liu, Michael F., et al.
Published: (2023)

Differentially Private Optimization for Non-Decomposable Objective Functions
by: Kong, Weiwei, et al.
Published: (2023)

Oracle-Efficient Differentially Private Learning with Public Data
by: Block, Adam, et al.
Published: (2024)