Personalized Differential Privacy

Latest papers

8 papers1 paper in the last four weeks, with none the four weeks before. 0.0% of all new papers.

Kinematics-Induced Multimodal 3D Human Pose Estimation with Subject-Level Privacy
Oct 2, 2026Kaushik Bhargav Sivangi, Fani DeligianniPersonalized Differential Privacy 3D Human Pose Estimation
Bio-AIm Lab School of Computing Science University of Glasgow
DCS: A Unified Conditional Sensitivity Framework for Cross-Modal Copyright Infringement Detection
Jul 24, 2026Xiafeng ManPersonalized Differential Privacy
Fudan University
Towards Personalized Differentially Private Learning for Decentralized Local Graphs
Jul 6, 2026Longzhu He, Peng Tang, Chaozhuo Li +5Graph Neural Networks Decentralized Learning
School of Computer Science, Beijing University of Posts and Telecommunications, Beijing 100876, China · State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China · School of Cyber Science and Technology, Shandong University, Qingdao, China +2
Limits of Personalizing Differential Privacy Budgets
May 13, 2026Edwige Cyffers, Juba ZianiDifferential Privacy Personalized Differential Privacy
CNRS, LAMSADE, Dauphine-PSL · Georgia Institute of Technology.
Privacy Preserving Machine Learning Workflow: from Anonymization to Personalized Differential Privacy Budgets in Federated Learning
May 4, 2026Judith Sáinz-Pardo Díaz, Álvaro López GarcíaPrivacy-Preserving ML Differentially Private Federated Learning
Amplified Patch-Level Differential Privacy for Free via Random Cropping
Mar 25, 2026Kaan Durmaz, Jan Schuchardt, Sebastian Schmidt +1Personalized Differential Privacy Privacy-Preserving ML
Technical University of Munich · Machine Learning Research, Morgan Stanley
Certified Per-Instance Unlearning Using Individual Sensitivity Bounds
Feb 17, 2026Hanna Benarroch, Jamal Atif, Olivier CappéPersonalized Differential Privacy Machine Unlearning
DI-ENS · CMAP
Differential Privacy as a Perk: Federated Learning over Multiple-Access Fading Channels with a Multi-Antenna Base Station
Oct 27, 2025Hao Liang, Haifeng Wen, Kaishun Wu +2Personalized Differential Privacy Over-the-Air Federated Learning
IoT Thrust, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, 511453, China · Department of ECE, The Hong Kong University of Science and Technology, HK SAR

Oct 2, 2026J/K move · Enter open · S save

Kinematics-Induced Multimodal 3D Human Pose Estimation with Subject-Level Privacy

Kaushik Bhargav Sivangi, Fani Deligianni

Bio-AIm Lab School of Computing Science University of Glasgow

Personalized Differential Privacy 3D Human Pose Estimation Multimodal Sensor Fusion Membership Inference Attacks Differential Privacy

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Multimodal 3D Human Pose Estimation (3D HPE) combines complementary information from RGB, LiDAR, and mmWave radar, but models trained on correlated observations from the same individuals, raise privacy risks overlooked by record level analysis. We present a unified framework for multimodal 3D HPE that couples kinematics-induced sensor fusion with subject level privacy auditing and private training. First, our multimodal model aligns modality specific joint representation, injects skeletal structure and adaptively aggregates complementary sensor evidence for accurate pose prediction. Second, we formulate a black-box subject membership inference attack for 3D HPE, complemented by an empirical pointwise maximal leakage analysis, which characterizes how individual attack score outcomes change inference about the membership outcome. Third, we instantiate user-level differential privacy via Action Temporal Stratification, a population weighted within-subject sampling strategy that enforces action and temporal coverage. We evaluate our framework on the MM-Fi dataset across three diverse experimental protocols. Source-code will be released upon acceptance.