Imagen de Portada

Federated Transfer Learning with Differential Privacy

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Li, Mengchu, Tian, Ye, Feng, Yang, Yu, Yi
Formato:	Preprint
Publicado:	2024
Materias:	Machine Learning Cryptography and Security Statistics Theory Methodology
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Mitigating Privacy-Utility Trade-off in Decentralized Federated Learning via $f$-Differential Privacy
por: Li, Xiang, et al.
Publicado: (2025)

Differentially Private Federated Learning: Servers Trustworthiness, Estimation, and Statistical Inference
por: Zhang, Zhe, et al.
Publicado: (2024)

Bayesian Adversarial Privacy
por: Bell, Cameron, et al.
Publicado: (2026)

Score Attack: A Lower Bound Technique for Optimal Differentially Private Learning
por: Cai, T. Tony, et al.
Publicado: (2023)

Differentially Private Inference for Longitudinal Linear Regression
por: Sopa, Getoar, et al.
Publicado: (2026)

Differentially Private Permutation Tests: Applications to Kernel Methods
por: Kim, Ilmun, et al.
Publicado: (2023)

Monitoring Violations of Differential Privacy over Time
por: Askin, Önder, et al.
Publicado: (2025)

Unbiased Statistical Estimation and Valid Confidence Intervals Under Differential Privacy
por: Covington, Christian, et al.
Publicado: (2021)

Nonparametric extensions of randomized response for private confidence sets
por: Waudby-Smith, Ian, et al.
Publicado: (2022)

PrIsing: Privacy-Preserving Peer Effect Estimation via Ising Model
por: Chakraborty, Abhinav, et al.
Publicado: (2024)

Differentially private projection-depth-based medians
por: Ramsay, Kelly, et al.
Publicado: (2023)

Concentrated Differential Privacy for Bandits
por: Azize, Achraf, et al.
Publicado: (2023)

A Statistical Viewpoint on Differential Privacy: Hypothesis Testing, Representation and Blackwell's Theorem
por: Su, Weijie J.
Publicado: (2024)

Sequentially Auditing Differential Privacy
por: González, Tomás, et al.
Publicado: (2025)

Auditing Differential Privacy in the Black-Box Setting
por: Shi, Kaining, et al.
Publicado: (2025)

Optimal Regret of Bernoulli Bandits under Global Differential Privacy
por: Azize, Achraf, et al.
Publicado: (2025)

Shifted Interpolation for Differential Privacy
por: Bok, Jinho, et al.
Publicado: (2024)

General-Purpose $f$-DP Estimation and Auditing in a Black-Box Setting
por: Askin, Önder, et al.
Publicado: (2025)

Attack-Aware Noise Calibration for Differential Privacy
por: Kulynych, Bogdan, et al.
Publicado: (2024)

Beyond the Calibration Point: Mechanism Comparison in Differential Privacy
por: Kaissis, Georgios, et al.
Publicado: (2024)

Differentially Private Joint Independence Test
por: Liu, Xingwei, et al.
Publicado: (2025)

CURATE: Scaling-up Differentially Private Causal Graph Discovery
por: Bhattacharjee, Payel, et al.
Publicado: (2024)

Simulation-based, Finite-sample Inference for Privatized Data
por: Awan, Jordan, et al.
Publicado: (2023)

On Differentially Private U Statistics
por: Chaudhuri, Kamalika, et al.
Publicado: (2024)

Differentially Private Manifold Denoising
por: Wu, Jiaqi, et al.
Publicado: (2026)

Differentially Private Best-Arm Identification
por: Azize, Achraf, et al.
Publicado: (2024)

Robust Unsupervised Multi-task and Transfer Learning on Gaussian Mixture Models
por: Tian, Ye, et al.
Publicado: (2022)

Privacy of SGD under Gaussian or Heavy-Tailed Noise: Guarantees without Gradient Clipping
por: Şimşekli, Umut, et al.
Publicado: (2024)

Optimal Classification-based Anomaly Detection with Neural Networks: Theory and Practice
por: Zhou, Tian-Yi, et al.
Publicado: (2024)

Differentially Private Sliced Inverse Regression: Minimax Optimality and Algorithm
por: Xia, Xintao, et al.
Publicado: (2024)

DP-SPRT: Differentially Private Sequential Probability Ratio Tests
por: Michel, Thomas, et al.
Publicado: (2025)

Privacy Preserving Adaptive Experiment Design
por: Li, Jiachun, et al.
Publicado: (2024)

Robustness Against Weak or Invalid Instruments: Exploring Nonlinear Treatment Models with Machine Learning
por: Guo, Zijian, et al.
Publicado: (2022)

Contraction of Locally Differentially Private Mechanisms
por: Asoodeh, Shahab, et al.
Publicado: (2022)

Contextual Dynamic Pricing: Algorithms, Optimality, and Local Differential Privacy Constraints
por: Zhao, Zifeng, et al.
Publicado: (2024)

Differentially Private Synthetic High-dimensional Tabular Stream
por: Kumar, Girish, et al.
Publicado: (2024)

A Survey on Differential Privacy for SpatioTemporal Data in Transportation Research
por: Bhadani, Rahul
Publicado: (2024)

Differentially Private E-Values
por: Csillag, Daniel, et al.
Publicado: (2025)

An Iterative Algorithm for Differentially Private $k$-PCA with Adaptive Noise
por: Düngler, Johanna, et al.
Publicado: (2025)

De-amplifying Bias from Differential Privacy in Language Model Fine-tuning
por: Srivastava, Sanjari, et al.
Publicado: (2024)