Browse studies, page 343

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Federated Learning Meets Fairness and Differential Privacy arXiv (Cornell University), 2021
Advancements in Federated Learning: Models, Methods, and Privacy arXiv (Cornell University), 2023
An Accuracy-Lossless Perturbation Method for Defending Privacy Attacks in Federated Learning arXiv (Cornell University), 2020
Sparsified Secure Aggregation for Privacy-Preserving Federated Learning arXiv (Cornell University), 2021
FLAP: Federated Learning with Attack and Privacy Awareness 2022
Local Differential Privacy based Federated Learning for Internet of Things arXiv (Cornell University), 2020
Privacy Leakage of Real-World Vertical Federated Learning arXiv (Cornell University), 2020
FedBot: Enhancing Privacy in Chatbots with Federated Learning arXiv (Cornell University), 2023
Information-Theoretic Privacy in Federated Submodel learning arXiv (Cornell University), 2020
Privacy and Efficiency of Communications in Federated Split Learning arXiv (Cornell University), 2023
Federated Learning with Differential Privacy for Sensitive Domains Preprints.org, 2025
Faithful Edge Federated Learning: Scalability and Privacy arXiv (Cornell University), 2021
Decepticons: Corrupted Transformers Breach Privacy in Federated Learning for Language Models arXiv (Cornell University), 2022
A Differential Privacy Framework for Federated Learning Zenodo (CERN European Organization for Nuclear Research), 2026
LDP-Fed: Federated Learning with Local Differential Privacy arXiv (Cornell University), 2020
PPFL: Privacy-preserving Federated Learning with Trusted Execution Environments arXiv (Cornell University), 2021
Practical and Bilateral Privacy-preserving Federated Learning arXiv (Cornell University), 2020
Practical Privacy Attacks on Vertical Federated Learning arXiv (Cornell University), 2020
Privacy-Friendly IoT: Does federated learning guarantee privacy? Research Square, 2023
A Game-theoretic Framework for Privacy-preserving Federated Learning arXiv (Cornell University), 2023
Distributed Differential Privacy for Federated Learning Zenodo (CERN European Organization for Nuclear Research), 2026
FedXGBoost: Privacy-Preserving XGBoost for Federated Learning arXiv (Cornell University), 2021
Privacy-Preserving Aggregation in Federated Learning: A Survey arXiv (Cornell University), 2022
Federated Learning with Heterogeneous Differential Privacy arXiv (Cornell University), 2021
Decentralized Federated Learning with Differential Privacy Zenodo (CERN European Organization for Nuclear Research), 2026
Privacy as Commodity: MFG-RegretNet for Large-Scale Privacy Trading in Federated Learning arXiv (Cornell University), 2026
Privacy-Preserving Blockchain-Based Federated Learning for IoT Devices arXiv (Cornell University), 2019
Privacy-preserving Decentralized Aggregation for Federated Learning arXiv (Cornell University), 2020
Local Differential Privacy for Federated Learning arXiv (Cornell University), 2022
Dynamic Differential Privacy for Federated Learning Zenodo (CERN European Organization for Nuclear Research), 2026
Anonymizing Data for Privacy-Preserving Federated Learning arXiv (Cornell University), 2020
Privacy-preserving Decentralized Federated Learning arXiv (Cornell University), 2020
Asynchronous Federated Learning with Differential Privacy for Edge Intelligence arXiv (Cornell University), 2019
On Safeguarding Privacy and Security in the Framework of Federated Learning arXiv (Cornell University), 2019
On the Efficiency of Privacy Attacks in Federated Learning arXiv (Cornell University), 2024
ERIS: Enhancing Privacy and Scalability in Federated Learning via Federated Shard Aggregation arXiv (Cornell University), 2026
Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection arXiv (Cornell University), 2019
Toward Robustness and Privacy in Federated Learning: Experimenting with Local and Central Differential Privacy arXiv (Cornell University), 2020
Hidden Data Privacy Breaches in Federated Learning arXiv (Cornell University), 2024
Federated Deep Learning with Bayesian Privacy arXiv (Cornell University), 2021
On Privacy and Personalization in Cross-Silo Federated Learning arXiv (Cornell University), 2022
Differential Privacy for Federated Learning Zenodo (CERN European Organization for Nuclear Research), 2026
On the Security & Privacy in Federated Learning arXiv (Cornell University), 2021
Local and Central Differential Privacy for Robustness and Privacy in Federated Learning arXiv (Cornell University), 2020
Privacy and Robustness in Federated Learning: Attacks and Defenses arXiv (Cornell University), 2020
Hierarchical Federated Learning with Privacy arXiv (Cornell University), 2022
Security and Privacy Issues of Federated Learning arXiv (Cornell University), 2023
A Federated Learning Framework for Privacy-Preserving Predictive Maintenance in Distributed Smart Manufacturing 2026
MediVault: An Auditable and Secure Federated Learning System for Privacy-Preserving Healthcare Collaboration 2026
Experimental Validation of a Federated Explainable Multi-Modal Transformer–GAN Framework with AutoML-Optimized Ensemble Learning for Bias-Resilient, Privacy-Preserving and Resource-Efficient Real-Time Disease Prediction Across Heterogeneous Multi-Site Populations 2026
Deep Learning Technologies for Real-Time Personalization in Mobile Applications 2026
Towards Transparent Rare Disease Monitoring: Federated Rule Extraction for Online Streaming NPC1 Data 2026
Secure and Privacy-Preserving Federated AI: A Robust Framework for Distributed Intelligence 2026
FedCRM-DP: A Privacy-Preserving Federated Learning Framework for Secure Cross-Organization CRM Intelligence 2026
Evaluating Federated Learning Under Data Heterogeneity: Failure Modes and Practical Mitigations 2026
Research on Federated Multimodal Human Morphology Recognition Integrating Convolutional and Graph Convolutional Networks 2026
MobiShield: Federated Android Malware Detection with Adaptive Differential Privacy under Concept Drift 2026
An Empirical Study of Stability and Fairness Side-Effects of Federated Unlearning for Departed Clients under Non-IID Data 2026
A Privacy-Preserving Federated Spatiotemporal Dynamic Graph Neural Network Framework for Epileptic Seizure Prediction 2026
FedDep-GT-LLM: Federated Graph Transformer and Clinical Language Modeling for Multimodal Depression Analysis 2026
NeuroFLAME: A Scalable, Privacy-Preserving Federated Learning Platform for Collaborative, Secure, and Reproducible Multi-Site Neuroimaging 2026
Defending Patient Privacy in Federated Learning with Shadow Model 2026
PRISM-VFL: A Differentially Private Vertical Federated Framework for Heterogeneous Multi-Task Clinical Prediction 2026
Dual-Layer PSO-Enhanced Federated Heterogeneous Data Fusion for Hemodialysis Complication Prediction 2026
Comparative Performance Evaluation of Federated Learning Frameworks for Edge-Oriented 6G Applications 2026
A Federated Learning Framework for Mental Stress Assessment and Brain Source Localization Using EEG and fNIRS 2026
Explainable Federated Multimodal Deep Learning Framework for Early Alzheimer’s Disease Detection: Integrating MRI, Clinical Data, and Expert-Guided Few-Shot Learning with Privacy-Preserving Cross-Site Validation 2026
Range-risk estimation for electric vehicles in low-coverage mountain road segments: A digital-twin study with prequential beacon-based Federated Learning 2026
FedMAPPO: Federated Multi-Agent Proximal Policy Optimization for Energy-Eﬃcient Task Oﬄoading in Industrial IoT Networks 2026
Federated Meta-Learning in the Time-Series Domain: a Scoping Review 2026
Privacy-Preserving Federated Learning for Cross-Dataset EEG-Based Detection of Parkinson's Disease 2026
Speech and Voice Biomarkers for Parkinson’s disease Detection: A Systematic Review of Machine Learning and Deep Learning Models 2026
OmniGuard V2X: A Hybrid-Security Prototype Framework with Assumption-Aware Validation for Smart Vehicle Systems 2026
Multi-Hospital Electronic Health Record Foundation Models Without Data Sharing: A Comparison of Federated Learning and Inference-Time Ensembling medRxiv : the preprint server for health sciences, 2026
Federated Learning Performance Depends on Site Variation in Global HIV Data Consortia medRxiv : the preprint server for health sciences, 2026
D3MI: an efficient and powerful federated imputation method for bias reduction in the analysis of distributed incomplete data by accounting for within-site correlation and between-site heterogeneity medRxiv : the preprint server for health sciences, 2025
Report of the Medical Image De-Identification (MIDI) Task Group -- Best Practices and Recommendations ArXiv, 2025
Development of a federated learning approach to predict acute kidney injury in adult hospitalized patients with COVID-19 in New York City medRxiv : the preprint server for health sciences, 2021
Federated Multiple Imputation for Variables that Are Missing Not At Random in Distributed Electronic Health Records medRxiv : the preprint server for health sciences, 2024
Federated Learning of Electronic Health Records Improves Mortality Prediction in Patients Hospitalized with COVID-19 medRxiv : the preprint server for health sciences, 2020
Training Together, Diagnosing Better: Federated Learning for Collagen VI-Related Dystrophies ArXiv, 2025
Federated Target Trial Emulation using Distributed Observational Data for Treatment Effect Estimation medRxiv : the preprint server for health sciences, 2025
Efficient Federated Learning for distributed NeuroImaging Data bioRxiv : the preprint server for biology, 2024
Federated prediction for scalable and privacy-preserved knowledge-based planning in radiotherapy ArXiv, 2025
Cumulus: A federated EHR-based learning system powered by FHIR and AI. medRxiv : the preprint server for health sciences, 2024
Advancing COVID-19 Diagnosis with Privacy-Preserving Collaboration in Artificial Intelligence ArXiv, 2021
Applications and challenges of biomarker-based predictive models in proactive health management Frontiers in public health, 2025
A Systematic Review of Cyber Threat Intelligence: The Effectiveness of Technologies, Strategies, and Collaborations in Combating Modern Threats Sensors (Basel, Switzerland), 2025
Applications of artificial intelligence in early childhood health management: a systematic review from fetal to pediatric periods Frontiers in pediatrics, 2025
Artificial intelligence in cardiopulmonary resuscitation: a systematic review Brazilian journal of anesthesiology (Elsevier), 2026
Harnessing AI in prosthodontics and implant dentistry: An umbrella review of systematic evidence Journal of prosthodontics : official journal of the American College of Prosthodontists, 2026
Deep learning applications in osteosarcoma MRI: A systematic review of recent advances in AI-based osteosarcoma diagnosis PloS one, 2026
Two-decade dialogue between artificial intelligence and osteoporosis: research trajectories and frontier projections under bibliometric and visual analysis Frontiers in medicine, 2025
Artificial Intelligence Platform Architecture for Hospital Systems: Systematic Review Journal of medical Internet research, 2025
A systematic review on the integration of explainable artificial intelligence in intrusion detection systems to enhancing transparency and interpretability in cybersecurity Frontiers in artificial intelligence, 2025
Machine learning approaches for EGFR mutation status prediction in NSCLC: an updated systematic review Frontiers in oncology, 2025
Spatio-Temporal COVID-19 Modeling: A Global Systematic Review of Data Integration, Equity, and Lessons for Pandemic Preparedness International journal of environmental research and public health, 2026
A PRISMA-based systematic review on advances in identity recognition and authentication using human biometric signals (2018-2023) Biomedical engineering online, 2026
The Micro-Mobility Sensing Gap: A Systematic Review of Physiological Safety Monitoring from Cycling to E-Scooters Sensors (Basel, Switzerland), 2026
Advancements in artificial intelligence transforming medical education: a comprehensive overview Medical education online, 2025