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Utility Optimization of Federated Learning with Differential Privacy
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/s11036-020-01586-4openalex-snapshot
FedMEC: Improving Efficiency of Differentially Private Federated Learning via Mobile Edge Computing
inferredcites →https://doi.org/10.1007/s12083-019-00869-2openalex-snapshot
Adaptive privacy-preserving federated learning
inferredcites →https://doi.org/10.1016/j.future.2020.10.007openalex-snapshot
A survey on security and privacy of federated learning
inferredcites →https://doi.org/10.1016/j.jnca.2014.02.012openalex-snapshot
Cooperative artificial bee colony algorithm for multi-objective RFID network planning
inferredcites →https://doi.org/10.1109/5.726791openalex-snapshot
Gradient-based learning applied to document recognition
inferredcites →https://doi.org/10.1109/cvpr.2017.195openalex-snapshot
Xception: Deep Learning with Depthwise Separable Convolutions
inferredcites →https://doi.org/10.1109/icde.2019.00063openalex-snapshot
Collecting and Analyzing Multidimensional Data with Local Differential Privacy
inferredcites →https://doi.org/10.1109/infocom41043.2020.9155494openalex-snapshot
Optimizing Federated Learning on Non-IID Data with Reinforcement Learning
inferredcites →https://doi.org/10.1109/jiot.2020.2991416openalex-snapshot
Personalized Federated Learning With Differential Privacy
inferredcites →https://doi.org/10.1109/jsac.2019.2904348openalex-snapshot
Adaptive Federated Learning in Resource Constrained Edge Computing Systems
inferredcites →https://doi.org/10.1109/mis.2020.2988525openalex-snapshot
A Secure Federated Transfer Learning Framework
inferredcites →https://doi.org/10.1109/msp.2020.2975749openalex-snapshot
Federated Learning: Challenges, Methods, and Future Directions
inferredcites →https://doi.org/10.1109/sp.2019.00019openalex-snapshot
Differentially Private Model Publishing for Deep Learning
inferredcites →https://doi.org/10.1109/sp.2019.00029openalex-snapshot
Exploiting Unintended Feature Leakage in Collaborative Learning
inferredcites →https://doi.org/10.1109/sp40000.2020.00025openalex-snapshot
The Value of Collaboration in Convex Machine Learning with Differential Privacy
inferredcites →https://doi.org/10.1109/tcyb.2020.3041212openalex-snapshot
An Adaptive Localized Decision Variable Analysis Approach to Large-Scale Multiobjective and Many-Objective Optimization
inferredcites →https://doi.org/10.1109/tcyb.2021.3086501openalex-snapshot
Learning to Optimize: Reference Vector Reinforcement Learning Adaption to Constrained Many-Objective Optimization of Industrial Copper Burdening System
inferredcites →https://doi.org/10.1109/tifs.2020.2988575openalex-snapshot
Federated Learning With Differential Privacy: Algorithms and Performance Analysis
inferredcites →https://doi.org/10.1109/tii.2019.2945367openalex-snapshot
Efficient and Privacy-Enhanced Federated Learning for Industrial Artificial Intelligence
inferredcites →https://doi.org/10.1109/tnnls.2019.2944481openalex-snapshot
Robust and Communication-Efficient Federated Learning From Non-i.i.d. Data
inferredcites →https://doi.org/10.1109/tsmc.2020.2963943openalex-snapshot
Enhancing Learning Efficiency of Brain Storm Optimization via Orthogonal Learning Design
inferredcites →https://doi.org/10.1145/2810103.2813677openalex-snapshot
Model Inversion Attacks that Exploit Confidence Information and Basic Countermeasures
inferredcites →https://doi.org/10.1145/3133956.3133982openalex-snapshot
Practical Secure Aggregation for Privacy-Preserving Machine Learning
inferredcites →https://doi.org/10.1145/3387107openalex-snapshot
Federated learning for privacy-preserving AI
inferredcites →https://doi.org/10.1561/0400000042openalex-snapshot
The Algorithmic Foundations of Differential Privacy
inferredcites →https://doi.org/10.48550/arxiv.1602.05629openalex-snapshot
Communication-Efficient Learning of Deep Networks from Decentralized Data
inferredcites →https://doi.org/10.48550/arxiv.1710.06963openalex-snapshot
Learning Differentially Private Recurrent Language Models
inferredcites →https://doi.org/10.48550/arxiv.1712.07557openalex-snapshot
Differentially Private Federated Learning: A Client Level Perspective
inferredcites →https://doi.org/10.48550/arxiv.1806.00582openalex-snapshot
Federated Learning with Non-IID Data
inferredcites →https://doi.org/10.48550/arxiv.1903.03934openalex-snapshot
Asynchronous Federated Optimization
inferredcites →https://doi.org/10.48550/arxiv.1905.03817openalex-snapshot
On the Linear Speedup Analysis of Communication Efficient Momentum SGD for Distributed Non-Convex Optimization
inferredcites →https://doi.org/10.48550/arxiv.1906.08320openalex-snapshot
Scalable and Differentially Private Distributed Aggregation in the Shuffled Model
inferredcites →https://doi.org/10.48550/arxiv.1907.02189openalex-snapshot
On the Convergence of FedAvg on Non-IID Data
inferredcites →https://doi.org/10.48550/arxiv.2103.00342openalex-snapshot
Constrained Differentially Private Federated Learning for Low-bandwidth Devices
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/s10462-024-10774-7openalex-snapshot
Survey: federated learning data security and privacy-preserving in edge-Internet of Things
inferred← citeshttps://doi.org/10.1016/j.jpdc.2024.104918openalex-snapshot
Balancing privacy and performance in federated learning: A systematic literature review on methods and metrics
inferred← citeshttps://doi.org/10.1038/s41598-024-70025-1openalex-snapshot
WFB: watermarking-based copyright protection framework for federated learning model via blockchain
inferred← citeshttps://doi.org/10.1063/5.0190663openalex-snapshot
Vertical federated learning with k-means and k-mode
inferred← citeshttps://doi.org/10.1080/08839514.2024.2410504openalex-snapshot
Privacy Issues, Attacks, Countermeasures and Open Problems in Federated Learning: A Survey
inferred← citeshttps://doi.org/10.1093/comjnl/bxae081openalex-snapshot
FDP-FL: differentially private federated learning with flexible privacy budget allocation
inferred← citeshttps://doi.org/10.1109/acdsa67686.2026.11468128openalex-snapshot
Hydro-DPFLQB: A Differentially Private Federated Learning-Assisted Quantum-Safe Blockchain Method for the Green Hydrogen Supply Chain
inferred← citeshttps://doi.org/10.1109/icccbda56900.2023.10154864openalex-snapshot
Federated Learning Differential Privacy Preservation Method Based on Differentiated Noise Addition
inferred← citeshttps://doi.org/10.1109/iccsie65832.2025.00032openalex-snapshot
Differentially Private Federated Learning: A Provably Secure Framework for Multi-Tenant Cloud AI Training
inferred← citeshttps://doi.org/10.1109/icrss65752.2024.00053openalex-snapshot
A Method for Protecting the Privacy of Massive Data Based on Differential Privacy
inferred← citeshttps://doi.org/10.1109/imcom64595.2025.10857505openalex-snapshot
A Theoretical Comparison of Federated Learning with Differential Privacy and Blockchain for Security and Privacy in IoMT
inferred← citeshttps://doi.org/10.1109/tbdata.2022.3225688openalex-snapshot
Research of Federated Learning Application Methods and Social Responsibility
inferred← citeshttps://doi.org/10.1109/tce.2023.3320122openalex-snapshot
AdaDpFed: A Differentially Private Federated Learning Algorithm With Adaptive Noise on Non-IID Data
inferred← citeshttps://doi.org/10.1109/tnnls.2024.3427789openalex-snapshot
Embracing Multiheterogeneity and Privacy Security Simultaneously: A Dynamic Privacy-Aware Federated Reinforcement Learning Approach
inferred← citeshttps://doi.org/10.1109/wifs66636.2025.00040openalex-snapshot
GAFIN: Gradient Direction-Agnostic Differential Privacy Control for Federated Learning via Nussbaum-Enhanced PID Tracking
inferred← citeshttps://doi.org/10.1145/3551663.3558682openalex-snapshot
Using Decentralized Aggregation for Federated Learning with Differential Privacy
inferred← citeshttps://doi.org/10.1145/3658664.3659655openalex-snapshot
Honest Fraction Differential Privacy
inferred← citeshttps://doi.org/10.1145/3731867.3731873openalex-snapshot
Efficient Federated Learning based on Hybrid Weights and Differential Privacy
inferred← citeshttps://doi.org/10.1145/3800684openalex-snapshot
Systematic Literature Review on Differential Privacy in Machine Learning
inferred← citeshttps://doi.org/10.1371/journal.pone.0344251openalex-snapshot
IVA-FL: An information-value-aware federated learning framework for Privacy-Preserving Financial data Risk Management
inferred← citeshttps://doi.org/10.2196/41588openalex-snapshot
Federated Machine Learning, Privacy-Enhancing Technologies, and Data Protection Laws in Medical Research: Scoping Review
inferred← citeshttps://doi.org/10.23919/icn.2024.0014openalex-snapshot
Crowdsourced Federated Learning Architecture with Personalized Privacy Preservation
inferred← citeshttps://doi.org/10.29304/jqcm.2022.14.4.1081openalex-snapshot
Mining Distributed Data using Vertical Federated Learning Review
inferred← citeshttps://doi.org/10.3390/electronics12204364openalex-snapshot
Consideration of FedProx in Privacy Protection
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