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Hierarchical Clustering-based Personalized Federated Learning for Robust and Fair Human Activity Recognition
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Algorithms for hierarchical clustering: an overview
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Data Poisoning Attacks Against Federated Learning Systems
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Human Activity Recognition on Smartphones Using a Multiclass Hardware-Friendly Support Vector Machine
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Fairness and accuracy in horizontal federated learning
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Deep learning for sensor-based activity recognition: A survey
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An efficient algorithm for a complete link method
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SmartWall: Novel RFID-Enabled Ambient Human Activity Recognition Using Machine Learning for Unobtrusive Health Monitoring
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Federated Learning in Mobile Edge Networks: A Comprehensive Survey
inferredcites →https://doi.org/10.1109/cvpr42600.2020.00024openalex-snapshot
Ego-Topo: Environment Affordances From Egocentric Video
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Towards Fair Federated Learning with Zero-Shot Data Augmentation
inferredcites →https://doi.org/10.1109/ijcnn48605.2020.9207469openalex-snapshot
Federated learning with hierarchical clustering of local updates to improve training on non-IID data
inferredcites →https://doi.org/10.1109/msp.2020.2975749openalex-snapshot
Federated Learning: Challenges, Methods, and Future Directions
inferredcites →https://doi.org/10.1109/thms.2014.2377111openalex-snapshot
Human Activity Recognition Process Using 3-D Posture Data
inferredcites →https://doi.org/10.1109/tnnls.2020.3015958openalex-snapshot
Clustered Federated Learning: Model-Agnostic Distributed Multitask Optimization Under Privacy Constraints
inferredcites →https://doi.org/10.1145/1390156openalex-snapshot
Proceedings of the 25th international conference on Machine learning - ICML '08
inferredcites →https://doi.org/10.1145/1964897.1964918openalex-snapshot
Activity recognition using cell phone accelerometers
inferredcites →https://doi.org/10.1145/2994551.2994569openalex-snapshot
Deep Learning for RFID-Based Activity Recognition
inferredcites →https://doi.org/10.1145/3267305.3267561openalex-snapshot
A Fresnel Diffraction Model Based Human Respiration Detection System Using COTS Wi-Fi Devices
inferredcites →https://doi.org/10.1145/3380985openalex-snapshot
A Systematic Study of Unsupervised Domain Adaptation for Robust Human-Activity Recognition
inferredcites →https://doi.org/10.1145/3442381.3450006openalex-snapshot
Meta-HAR: Federated Representation Learning for Human Activity Recognition
inferredcites →https://doi.org/10.1145/3447744openalex-snapshot
Deep Learning for Sensor-based Human Activity Recognition
inferredcites →https://doi.org/10.1145/3448074openalex-snapshot
Unsupervised Human Activity Representation Learning with Multi-task Deep Clustering
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A Survey on Deep Learning for Human Activity Recognition
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Detecting Smartwatch-Based Behavior Change in Response to a Multi-Domain Brain Health Intervention
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Advances and Open Problems in Federated Learning
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Hierarchical Cluster Analysis: Comparison of Three Linkage Measures and Application to Psychological Data
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Federated Learning with Fair Averaging
inferredcites →https://doi.org/10.48550/arxiv.2011.10464openalex-snapshot
A Reputation Mechanism Is All You Need: Collaborative Fairness and Adversarial Robustness in Federated Learning
inferredcites →https://doi.org/10.5220/0005792401430151openalex-snapshot
The MobiAct Dataset: Recognition of Activities of Daily Living using Smartphones
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Unseen-aware semi-supervised model for robust human activity recognition
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A systematic survey on clustering in federated learning
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Federated Active User Participation (FAUP)
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Personalized federated learning with fairness, robustness, and collaboration incentives
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A comprehensive survey on client selection strategies in federated learning
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Model optimization techniques in personalized federated learning: A survey
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FeL-MAR: Federated learning based multi resident activity recognition in IoT enabled smart homes
inferred← citeshttps://doi.org/10.1016/j.inffus.2024.102756openalex-snapshot
FairDPFL-SCS: Fair Dynamic Personalized Federated Learning with strategic client selection for improved accuracy and fairness
inferred← citeshttps://doi.org/10.1016/j.jestch.2025.102230openalex-snapshot
DC-PFL: A dynamic clustering-based personalized federated learning method for human activity recognition
inferred← citeshttps://doi.org/10.1016/j.knosys.2024.112317openalex-snapshot
To be global or personalized: Generalized federated learning with cooperative adaptation for data heterogeneity
inferred← citeshttps://doi.org/10.1016/j.pmcj.2026.102163openalex-snapshot
TCP-HAR: On-Device Transferable and Copyright-Preserving Human Activity Recognition
inferred← citeshttps://doi.org/10.1109/bigdata66926.2025.11401842openalex-snapshot
SGFusion: Stochastic Geographic Gradient Fusion in Federated Learning
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LiCAFeL-STC: A Lightweight Cluster-Based Federated Learning Framework for Sensor-Based Human Activity Recognition Using Unlabeled Data in Heterogeneous Wearable Devices
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Transitioning From Federated Learning to Quantum Federated Learning in Internet of Things: A Comprehensive Survey
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FedCIM: Handling Data Heterogeneity in Federated Learning to Improve Fairness and Robustness
inferred← citeshttps://doi.org/10.1109/globecom52923.2024.10901296openalex-snapshot
Multi-Positive Sample Quantum Contrastive Learning for Human Activity Recognition
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A Review on Hierarchical Federated Learning: Architectures and Learning Algorithms
inferred← citeshttps://doi.org/10.1109/icaice68195.2025.11382392openalex-snapshot
GFPFL: A Group-Based Fair and Personalized Federated Learning Framework
inferred← citeshttps://doi.org/10.1109/icamechs63130.2024.10818732openalex-snapshot
A Comparative Study of Clustering Distance Metrics for Personalized Federated Learning in Human Activity Recognition
inferred← citeshttps://doi.org/10.1109/ie61493.2024.10599924openalex-snapshot
Multi-Frequency Federated Learning for Human Activity Recognition Using Head-Worn Sensors
inferred← citeshttps://doi.org/10.1109/infocom59046.2026.11571699openalex-snapshot
AHE: Adaptive Homomorphic Encryption for Customizable Privacy in Heterogeneous Federated Learning
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Personalized Federated Learning for Wearable Time-Series Health Monitoring: Methods, Challenges, and Future Directions
inferred← citeshttps://doi.org/10.1109/iwqos65803.2025.11143429openalex-snapshot
Correlation-Aware Multi-Similarity Learning for Federated Human Activity Recognition
inferred← citeshttps://doi.org/10.1109/jiot.2025.3573796openalex-snapshot
Thompson Sampling Policy for Dynamic Participating Client Scenario in Federated Learning
inferred← citeshttps://doi.org/10.1109/jiot.2025.3598149openalex-snapshot
FedCDC: Efficient Similarity Identification in Clustered Federated Learning via Community Detection on Non-IID Data
inferred← citeshttps://doi.org/10.1109/jiot.2025.3617794openalex-snapshot
Human–Machine Hybrid Federated Learning: Concept and Applications
inferred← citeshttps://doi.org/10.1109/jiot.2026.3695103openalex-snapshot
Energy- and AoI-Aware Hierarchical Personalized Federated Learning for Distributed Edge Systems With Selective LLM Module Exchange
inferred← citeshttps://doi.org/10.1109/jiot.2026.3697298openalex-snapshot
Personalizing Federated Learning for Hierarchical Edge Networks With Non-IID Data
inferred← citeshttps://doi.org/10.1109/jiot.2026.3720264openalex-snapshot
Prototype-Centered Residual Modeling for Federated Wireless Human Activity Recognition
inferred← citeshttps://doi.org/10.1109/ojcoms.2024.3484228openalex-snapshot
Federated Learning for Human Activity Recognition: Overview, Advances, and Challenges
inferred← citeshttps://doi.org/10.1109/percomworkshops59983.2024.10503023openalex-snapshot
Exploring Activity Recognition in Multi-device Environments using Hierarchical Federated Learning
inferred← citeshttps://doi.org/10.1109/seai65851.2025.11108905openalex-snapshot
HisHFL: Enhancing Hierarchical Federated Learning Security through Historical Knowledge
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pFedBL: Federated Bayesian Learning With Personalized Prior
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Personalized Model Partitioning and Aggregation for Federated Human Activity Recognition
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Democratizing Federated WiFi-Based Human Activity Recognition Using Hypothesis Transfer
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ClassTer: Mobile Shift-Robust Personalized Federated Learning via Class-Wise Clustering
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FedPriv: Personalized Differential Privacy in Federated Learning for Heterogeneous Data
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Dynamic Grouping and Aggregation Weight Optimization for Hierarchical Federated Learning With Quantization
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Bias Mitigation in Federated Learning for Edge Computing
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Enhancing On-Device LLM Inference with Historical Cloud-Based LLM Interactions
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CASA: Clustered Federated Learning with Asynchronous Clients
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CrossHAR: Generalizing Cross-dataset Human Activity Recognition via Hierarchical Self-Supervised Pretraining
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Label Leakage in Federated Inertial-based Human Activity Recognition
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From Verbal Reports to Personalized Activity Trackers: Understanding the Challenges of Ground Truth Data Collection with Older Adults in the Wild
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TraceRing: Touchpad-like Pointing with a Single IMU Ring through Personalized Learning
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CurvFed: Curvature-Aligned Federated Learning for Fairness without Demographics
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CHE-FL: Cluster-Based Hierarchical Federated Learning with Enhanced Robustness and Efficiency
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Hierarchical Aggregation for Federated Learning in Heterogeneous IoT Scenarios: Enhancing Privacy and Communication Efficiency
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Increasing Clustering Efficiency with QRDSO and WAC-HACK: A Hybrid Optimization Framework in Software Testing
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