Differentially Private Fisher Randomization Tests for Binary Outcomes Qingyang Sun, Jerome P. Reiter http://arxiv.org/abs/2511.20884

Road Network-Aware Personalized Trajectory Protection with Differential Privacy under Spatiotemporal Correlations Minghui Min, Jiahui Liu, Mingge Cao, Shiyin Li, Hongliang Zhang, Miao Pan, Zhu Han http://arxiv.org/abs/2511.21020

Data Exfiltration by Compression Attack: Definition and Evaluation on Medical Image Data Huiyu Li, Nicholas Ayache, Hervé Delingette http://arxiv.org/abs/2511.21227

Differentially Private Computation of the Gini Index for Income Inequality Wenjie Lan, Jerome P. Reiter http://arxiv.org/abs/2511.19771

N2E: A General Framework to Reduce Node-Differential Privacy to Edge-Differential Privacy for Graph Analytics Yihua Hu, Hao Ding, Wei Dong http://arxiv.org/abs/2511.20125

DP-MicroAdam: Private and Frugal Algorithm for Training and Fine-tuning Mihaela Hudişteanu, Edwige Cyffers, Nikita P. Kalinin http://arxiv.org/abs/2511.20509

Learning Rate Scheduling with Matrix Factorization for Private Training Nikita P. Kalinin, Joel Daniel Andersson http://arxiv.org/abs/2511.17994

Understanding Private Learning From Feature Perspective Meng Ding, Mingxi Lei, Shaopeng Fu, Shaowei Wang, Di Wang, Jinhui Xu http://arxiv.org/abs/2511.18006

Correlated-Sequence Differential Privacy Yifan Luo, Meng Zhang, Jin Xu, Junting Chen, Jianwei Huang http://arxiv.org/abs/2511.18025

Differential privacy with dependent data Valentin Roth, Marco Avella-Medina http://arxiv.org/abs/2511.18583

Fairness Meets Privacy: Integrating Differential Privacy and Demographic Parity in Multi-class Classification Lilian Say, Christophe Denis, Rafael Pinot http://arxiv.org/abs/2511.18876

A General Framework for Per-record Differential Privacy Xinghe Chen, Dajun Sun, Quanqing Xu, Wei Dong http://arxiv.org/abs/2511.19015

Membership Inference Attacks Beyond Overfitting Mona Khalil, Alberto Blanco-Justicia, Najeeb Jebreel, Josep Domingo-Ferrer http://arxiv.org/abs/2511.16792

Differentially private testing for relevant dependencies in high dimensions Patrick Bastian, Holger Dette, Martin Dunsche http://arxiv.org/abs/2511.17167

🤖 Posts have been a bit erratic lately. This is due to an update to the arXiv API. It should get fixed soon. In the meantime, we've been trying to mitigate the issues. 🤖

Optimal Fairness under Local Differential Privacy Hrad Ghoukasian, Shahab Asoodeh http://arxiv.org/abs/2511.16377

Almost Sure Convergence Analysis of Differentially Private Stochastic Gradient Methods Amartya Mukherjee, Jun Liu http://arxiv.org/abs/2511.16587

How to Train Private Clinical Language Models: A Comparative Study of Privacy-Preserving Pipelines for ICD-9 Coding Mathieu Dufour, Andrew Duncan http://arxiv.org/abs/2511.14936

Mutual Information Bounds in the Shuffle Model Pengcheng Su, Haibo Cheng, Ping Wang http://arxiv.org/abs/2511.15051

Privacy-Preserving IoT in Connected Aircraft Cabin Nilesh Vyas, Benjamin Zhao, Aygün Baltaci, Gustavo de Carvalho Bertoli, Hassan Asghar, Markus Klügel, Gerrit Schramm, Martin Kubisch, Dali Kaafar http://arxiv.org/abs/2511.15278

Rényi Differential Privacy for Heavy-Tailed SDEs via Fractional Poincaré Inequalities Benjamin Dupuis, Mert Gürbüzbalaban, Umut Şimşekli, Jian Wang, Sinan Yildirim, Lingjiong Zhu http://arxiv.org/abs/2511.15634

Beyond One-Size-Fits-All: Neural Networks for Differentially Private Tabular Data Synthesis Kai Chen, Chen Gong, Tianhao Wang http://arxiv.org/abs/2511.13893

On the Gradient Complexity of Private Optimization with Private Oracles Michael Menart, Aleksandar Nikolov http://arxiv.org/abs/2511.13999

Observational Auditing of Label Privacy Iden Kalemaj, Luca Melis, Maxime Boucher, Ilya Mironov, Saeed Mahloujifar http://arxiv.org/abs/2511.14084

Whistledown: Combining User-Level Privacy with Conversational Coherence in LLMs Chelsea McMurray, Hayder Tirmazi http://arxiv.org/abs/2511.13319

Tight and Practical Privacy Auditing for Differentially Private In-Context Learning Yuyang Xia, Ruixuan Liu, Li Xiong http://arxiv.org/abs/2511.13502

Privacy protection under the exposure of systems' prior information Le Liu, Yu Kawano, Ming Cao http://arxiv.org/abs/2511.10771

Private Zeroth-Order Optimization with Public Data Xuchen Gong, Tian Li http://arxiv.org/abs/2511.10859

Improved Differentially Private Algorithms for Rank Aggregation Quentin Hillebrand, Pasin Manurangsi, Vorapong Suppakitpaisarn, Phanu Vajanopath http://arxiv.org/abs/2511.11319

Private Frequency Estimation Via Residue Number Systems Héber H. Arcolezi http://arxiv.org/abs/2511.11569

SWIR-LightFusion: Multi-spectral Semantic Fusion of Synthetic SWIR with Thermal IR (LWIR/MWIR) and RGB Muhammad Ishfaq Hussain, Ma Van Linh, Zubia Naz, Unse Fatima, Yeongmin Ko, Moongu Jeon http://arxiv.org/abs/2510.13404

Robust or Suggestible? Exploring Non-Clinical Induction in LLM Drug-Safety Decisions Siying Liu, Shisheng Zhang, Indu Bala http://arxiv.org/abs/2510.13931

MAGIC-Flow: Multiscale Adaptive Conditional Flows for Generation and Interpretable Classification Luca Caldera, Giacomo Bottacini, Lara Cavinato http://arxiv.org/abs/2510.22070

Beyond Uniform Deletion: A Data Value-Weighted Framework for Certified Machine Unlearning Lisong He, Yi Yang, Xiangyu Chang http://arxiv.org/abs/2511.06794

Achieving Effective Virtual Reality Interactions via Acoustic Gesture Recognition based on Large Language Models Xijie Zhang, Fengliang He, Hong-Ning Dai http://arxiv.org/abs/2511.07085

Biologically-Informed Hybrid Membership Inference Attacks on Generative Genomic Models Asia Belfiore, Jonathan Passerat-Palmbach, Dmitrii Usynin http://arxiv.org/abs/2511.07503

Private-RAG: Answering Multiple Queries with LLMs while Keeping Your Data Private Ruihan Wu, Erchi Wang, Zhiyuan Zhang, Yu-Xiang Wang http://arxiv.org/abs/2511.07637

DP-AdamW: Investigating Decoupled Weight Decay and Bias Correction in Private Deep Learning Jay Chooi, Kevin Cong, Russell Li, Lillian Sun http://arxiv.org/abs/2511.07843

PrAda-GAN: A Private Adaptive Generative Adversarial Network with Bayes Network Structure Ke Jia, Yuheng Ma, Yang Li, Feifei Wang http://arxiv.org/abs/2511.07997

Demystifying QUIC from the Specifications Darius Saif, Ashraf Matrawy http://arxiv.org/abs/2511.08375

FAIRPLAI: A Human-in-the-Loop Approach to Fair and Private Machine Learning David Sanchez, Holly Lopez, Michelle Buraczyk, Anantaa Kotal http://arxiv.org/abs/2511.08702

Enhancing DPSGD via Per-Sample Momentum and Low-Pass Filtering Xincheng Xu, Thilina Ranbaduge, Qing Wang, Thierry Rakotoarivelo, David Smith http://arxiv.org/abs/2511.08841

Differentially Private Rankings via Outranking Methods and Performance Data Aggregation Luis Del Vasto-Terrientes http://arxiv.org/abs/2511.09120

Abstract Gradient Training: A Unified Certification Framework for Data Poisoning, Unlearning, and Differential Privacy Philip Sosnin, Matthew Wicker, Josh Collyer, Calvin Tsay http://arxiv.org/abs/2511.09400

GEM+: Scalable State-of-the-Art Private Synthetic Data with Generator Networks Samuel Maddock, Shripad Gade, Graham Cormode, Will Bullock http://arxiv.org/abs/2511.09672

Cooperative Local Differential Privacy: Securing Time Series Data in Distributed Environments Bikash Chandra Singh, Md Jakir Hossain, Rafael Diaz, Sandip Roy, Ravi Mukkamala, Sachin Shetty http://arxiv.org/abs/2511.09696

DP-GENG : Differentially Private Dataset Distillation Guided by DP-Generated Data Shuo Shi, Jinghuai Zhang, Shijie Jiang, Chunyi Zhou, Yuyuan Li, Mengying Zhu, Yangyang Wu, Tianyu Du http://arxiv.org/abs/2511.09876

Simulator and Experience Enhanced Diffusion Model for Comprehensive ECG Generation Xiaoda Wang, Kaiqiao Han, Yuhao Xu, Xiao Luo, Yizhou Sun, Wei Wang, Carl Yang http://arxiv.org/abs/2511.09895

Privacy Structure and Blackwell Frontier Zhang Xu, Wei Zhao http://arxiv.org/abs/2511.10226

Setting $ varepsilon$ is not the Issue in Differential Privacy Edwige Cyffers http://arxiv.org/abs/2511.06305