Differentially Private Log-Location-Scale Regression Using Functional Mechanism
Fuente:
arXiv
Guardado en:
| Autores principales: | Sheng, Jiewen, Fang, Xiaolei |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Differentially Private Modeling of Disease Transmission within Human Contact Networks
por: Hod, Shlomi, et al.
Publicado: (2026)
por: Hod, Shlomi, et al.
Publicado: (2026)
Inference With Combining Rules From Multiple Differentially Private Synthetic Datasets
por: Nombo, Leila, et al.
Publicado: (2024)
por: Nombo, Leila, et al.
Publicado: (2024)
Analyzing the Differentially Private Theil-Sen Estimator for Simple Linear Regression
por: Sarathy, Jayshree, et al.
Publicado: (2022)
por: Sarathy, Jayshree, et al.
Publicado: (2022)
An algorithm for forensic toolmark comparisons
por: Cuellar, Maria, et al.
Publicado: (2023)
por: Cuellar, Maria, et al.
Publicado: (2023)
Releasing Differentially Private Event Logs Using Generative Models
por: Wangelik, Frederik, et al.
Publicado: (2025)
por: Wangelik, Frederik, et al.
Publicado: (2025)
Watermarking Generative Tabular Data
por: He, Hengzhi, et al.
Publicado: (2024)
por: He, Hengzhi, et al.
Publicado: (2024)
Why You Should Not Trust Interpretations in Machine Learning: Adversarial Attacks on Partial Dependence Plots
por: Xin, Xi, et al.
Publicado: (2024)
por: Xin, Xi, et al.
Publicado: (2024)
Indiscriminate Disruption of Conditional Inference on Multivariate Gaussians
por: Caballero, William N., et al.
Publicado: (2024)
por: Caballero, William N., et al.
Publicado: (2024)
Bridging Unsupervised and Semi-Supervised Anomaly Detection: A Theoretically-Grounded and Practical Framework with Synthetic Anomalies
por: Lau, Matthew, et al.
Publicado: (2025)
por: Lau, Matthew, et al.
Publicado: (2025)
Attacker Behaviour Profiling using Stochastic Ensemble of Hidden Markov Models
por: Deshmukh, Soham, et al.
Publicado: (2019)
por: Deshmukh, Soham, et al.
Publicado: (2019)
Automated Alert Classification and Triage (AACT): An Intelligent System for the Prioritisation of Cybersecurity Alerts
por: Turcotte, Melissa, et al.
Publicado: (2025)
por: Turcotte, Melissa, et al.
Publicado: (2025)
Private Linear Regression with Differential Privacy and PAC Privacy
por: Yang, Hillary, et al.
Publicado: (2024)
por: Yang, Hillary, et al.
Publicado: (2024)
Privately Learning Decision Lists and a Differentially Private Winnow
por: Bun, Mark, et al.
Publicado: (2026)
por: Bun, Mark, et al.
Publicado: (2026)
Noise-Aware Differentially Private Regression via Meta-Learning
por: Räisä, Ossi, et al.
Publicado: (2024)
por: Räisä, Ossi, et al.
Publicado: (2024)
Differentially Private Sparse Linear Regression with Heavy-tailed Responses
por: Tian, Xizhi, et al.
Publicado: (2025)
por: Tian, Xizhi, et al.
Publicado: (2025)
Correlated Noise Mechanisms for Differentially Private Learning
por: Pillutla, Krishna, et al.
Publicado: (2025)
por: Pillutla, Krishna, et al.
Publicado: (2025)
Scaling Laws for Differentially Private Language Models
por: McKenna, Ryan, et al.
Publicado: (2025)
por: McKenna, Ryan, et al.
Publicado: (2025)
Privacy-Preserving Customer Support: A Framework for Secure and Scalable Interactions
por: Awasthi, Anant Prakash, et al.
Publicado: (2024)
por: Awasthi, Anant Prakash, et al.
Publicado: (2024)
Methods for generating and evaluating synthetic longitudinal patient data: a systematic review
por: Perkonoja, Katariina, et al.
Publicado: (2023)
por: Perkonoja, Katariina, et al.
Publicado: (2023)
Differentially Private Release and Learning of Threshold Functions
por: Bun, Mark, et al.
Publicado: (2015)
por: Bun, Mark, et al.
Publicado: (2015)
Accuracy Improvement in Differentially Private Logistic Regression: A Pre-training Approach
por: Hoseinpour, Mohammad, et al.
Publicado: (2023)
por: Hoseinpour, Mohammad, et al.
Publicado: (2023)
Differentially Private Optimization for Non-Decomposable Objective Functions
por: Kong, Weiwei, et al.
Publicado: (2023)
por: Kong, Weiwei, et al.
Publicado: (2023)
Private and Collaborative Kaplan-Meier Estimators
por: Rahimian, Shadi, et al.
Publicado: (2023)
por: Rahimian, Shadi, et al.
Publicado: (2023)
Differentially Private Post-Processing for Fair Regression
por: Xian, Ruicheng, et al.
Publicado: (2024)
por: Xian, Ruicheng, et al.
Publicado: (2024)
DPIS: An Enhanced Mechanism for Differentially Private SGD with Importance Sampling
por: Wei, Jianxin, et al.
Publicado: (2022)
por: Wei, Jianxin, et al.
Publicado: (2022)
Bayesian Pseudo Posterior Mechanism for Differentially Private Machine Learning
por: Chew, Robert, et al.
Publicado: (2025)
por: Chew, Robert, et al.
Publicado: (2025)
Privacy-Preserving Cohort Analytics for Personalized Health Platforms: A Differentially Private Framework with Stochastic Risk Modeling
por: Chakraborty, Richik, et al.
Publicado: (2026)
por: Chakraborty, Richik, et al.
Publicado: (2026)
Pre-training Differentially Private Models with Limited Public Data
por: Bu, Zhiqi, et al.
Publicado: (2024)
por: Bu, Zhiqi, et al.
Publicado: (2024)
Position: Considerations for Differentially Private Learning with Large-Scale Public Pretraining
por: Tramèr, Florian, et al.
Publicado: (2022)
por: Tramèr, Florian, et al.
Publicado: (2022)
Differentially Private Iterative Screening Rules for Linear Regression
por: Khanna, Amol, et al.
Publicado: (2025)
por: Khanna, Amol, et al.
Publicado: (2025)
Bridging Data Barriers among Participants: Assessing the Potential of Geoenergy through Federated Learning
por: Peng, Weike, et al.
Publicado: (2024)
por: Peng, Weike, et al.
Publicado: (2024)
Machine Learning for Network Attacks Classification and Statistical Evaluation of Adversarial Learning Methodologies for Synthetic Data Generation
por: Zarkadis, Iakovos-Christos, et al.
Publicado: (2026)
por: Zarkadis, Iakovos-Christos, et al.
Publicado: (2026)
PRIMO: Private Regression in Multiple Outcomes
por: Neel, Seth
Publicado: (2023)
por: Neel, Seth
Publicado: (2023)
Differentially Private Inference for Longitudinal Linear Regression
por: Sopa, Getoar, et al.
Publicado: (2026)
por: Sopa, Getoar, et al.
Publicado: (2026)
Differentially Private Sliced Inverse Regression: Minimax Optimality and Algorithm
por: Xia, Xintao, et al.
Publicado: (2024)
por: Xia, Xintao, et al.
Publicado: (2024)
Mitigating Noise Detriment in Differentially Private Federated Learning with Model Pre-training
por: Jin, Huitong, et al.
Publicado: (2024)
por: Jin, Huitong, et al.
Publicado: (2024)
Scaling up the Banded Matrix Factorization Mechanism for Differentially Private ML
por: McKenna, Ryan
Publicado: (2024)
por: McKenna, Ryan
Publicado: (2024)
Delving into Differentially Private Transformer
por: Ding, Youlong, et al.
Publicado: (2024)
por: Ding, Youlong, et al.
Publicado: (2024)
Differentially Private Attention Computation
por: Gao, Yeqi, et al.
Publicado: (2023)
por: Gao, Yeqi, et al.
Publicado: (2023)
Differentially Private Diffusion Models
por: Dockhorn, Tim, et al.
Publicado: (2022)
por: Dockhorn, Tim, et al.
Publicado: (2022)
Ejemplares similares
-
Differentially Private Modeling of Disease Transmission within Human Contact Networks
por: Hod, Shlomi, et al.
Publicado: (2026) -
Inference With Combining Rules From Multiple Differentially Private Synthetic Datasets
por: Nombo, Leila, et al.
Publicado: (2024) -
Analyzing the Differentially Private Theil-Sen Estimator for Simple Linear Regression
por: Sarathy, Jayshree, et al.
Publicado: (2022) -
An algorithm for forensic toolmark comparisons
por: Cuellar, Maria, et al.
Publicado: (2023) -
Releasing Differentially Private Event Logs Using Generative Models
por: Wangelik, Frederik, et al.
Publicado: (2025)