H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications | Paper Citation Record

Observation 89191949-06d4-4eff-8d70-2f18949dd44e · outbound

This paper cites Srda: Mobile sensing based fluid overload detection for end stage kidney disease patients using sensor relation dual autoencoder,.

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications Srda: Mobile sensing based fluid overload detection for end stage kidney disease patients using sensor relation dual autoencoder,

Reference 1

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Observation 8aabe46c-8b69-4fef-a592-e712d8a2e3ba · outbound

This paper cites Pfdrl: Personalized federated deep reinforcement learning for residen- tial energy management,.

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications Pfdrl: Personalized federated deep reinforcement learning for residen- tial energy management,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:01:19.778072Z

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Observation b40ff76f-63e2-491a-91ed-be50ea3ede92 · outbound

This paper cites Federated machine learning: Concept and applications,.

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications Federated machine learning: Concept and applications,

Reference 3

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Observation 435e33ac-48e3-48e6-9d75-4daef3ff0bd3 · outbound

This paper cites Communication-efficient learning of deep networks from decentralized data,.

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications Communication-efficient learning of deep networks from decentralized data,

Reference 4

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This paper cites Federated optimization in heterogeneous networks,.

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications Federated optimization in heterogeneous networks,

Reference 5

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This paper cites Scaffold: Stochastic controlled averaging for federated learn- ing,.

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications Scaffold: Stochastic controlled averaging for federated learn- ing,

Reference 6

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This paper cites Understanding the smart city domain: A literature review,.

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications Understanding the smart city domain: A literature review,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:01:19.603959Z

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Observation d3ea8b36-169b-48b4-92a5-44e7de9a1873 · outbound

This paper cites Smart farming: An overview,.

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications Smart farming: An overview,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:01:19.570039Z

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Observation 8e3927ae-3f68-4882-b68e-5d35b5d0aee9 · outbound

This paper cites Client-edge-cloud hierarchical federated learning,.

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications Client-edge-cloud hierarchical federated learning,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:01:19.527260Z

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This paper cites Federated learning with extreme label skew: A data extension approach,.

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications Federated learning with extreme label skew: A data extension approach,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:01:19.477886Z

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Observation 983549b5-2e21-4aff-9c26-88f6a0e91530 · outbound

This paper cites Federated learning technology in serial topology for iot networks,.

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications Federated learning technology in serial topology for iot networks,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:01:19.446953Z

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Observation 440dd7fc-d421-4e42-9bb7-085070970e8f · outbound

This paper cites Artificial intelligence-aided digital twin design: A systematic review,.

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications Artificial intelligence-aided digital twin design: A systematic review,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:01:19.417681Z

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This paper cites FedBCGD: Communication-efficient accelerated block coordinate gradient descent for federated learning,.

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications FedBCGD: Communication-efficient accelerated block coordinate gradient descent for federated learning,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:01:19.371986Z

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This paper cites A model parameter update strategy for enhanced asynchronous federated learning algorithm,.

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications A model parameter update strategy for enhanced asynchronous federated learning algorithm,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:01:19.336912Z

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Observation b59a1421-160e-4226-b0dd-8de309d39a47 · outbound

This paper cites Personalized Federated Learning: A Meta-Learning Approach.

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications Personalized Federated Learning: A Meta-Learning Approach

Reference 15

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Observation 8b523a0a-d3b5-42c5-82b8-1eb20b9030d7 · outbound

This paper cites Ternary compression for communication-efficient federated learning,.

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications Ternary compression for communication-efficient federated learning,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:01:19.289088Z

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Observation a4efb0da-142d-4e7f-b093-ea75379590b2 · outbound

This paper cites Communication-Efficient Adaptive Federated Learning.

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications Communication-Efficient Adaptive Federated Learning

Reference 17

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This paper cites Fedrs: Federated learning with restricted softmax for label distribution non-iid data,.

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications Fedrs: Federated learning with restricted softmax for label distribution non-iid data,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-11T20:01:17.789187Z

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Observation f648a410-df41-4a70-ace4-c911856bfcd1 · outbound

This paper cites Federated Learning with Personalization Layers.

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications Federated Learning with Personalization Layers

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-11T20:01:17.798949Z

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Observation 0072cb6a-fa41-4acd-a18f-d92b9ecb3a96 · outbound

This paper cites Smartphone and smartwatch-based biometrics using activities of daily living,.

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications Smartphone and smartwatch-based biometrics using activities of daily living,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:01:19.255121Z

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Observation 1f095aeb-6f8d-42de-870d-25e724f01ae5 · outbound

This paper cites Widar 3.0: Wifi-based activity recognition dataset,.

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications Widar 3.0: Wifi-based activity recognition dataset,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-11T20:01:17.814026Z

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Observation 212a1a45-06de-4262-9e28-d7db5d28360c · outbound

This paper cites Zero-effort cross-domain gesture recognition with wi-fi,.

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications Zero-effort cross-domain gesture recognition with wi-fi,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-11T20:01:17.821159Z

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This paper cites Design considerations for the wisdm smart phone-based sensor mining architecture,.

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications Design considerations for the wisdm smart phone-based sensor mining architecture,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:01:19.201374Z

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Observation 870e2c3e-c1cc-412a-8db8-5dfd10474498 · outbound

This paper cites Gradient-based learning applied to document recognition,.

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications Gradient-based learning applied to document recognition,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-11T20:01:17.842737Z

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Observation 45cf2cf3-1a03-4396-8e1a-d8a21bb96f54 · outbound

This paper cites Federated learning on non-iid data silos: An experimental study,.

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications Federated learning on non-iid data silos: An experimental study,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-11T20:01:17.856347Z

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Observation 9c6fe8db-1620-4485-b30f-d80abebfce85 · outbound

This paper cites Sparse Communication for Distributed Gradient Descent.

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications Sparse Communication for Distributed Gradient Descent

Reference 26

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This paper cites Industrial automation using iot,.

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications Industrial automation using iot,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:01:19.133089Z

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This paper cites A review on iot healthcare monitoring applications and a vision for transforming sensor data into real-time clinical feedback,.

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications A review on iot healthcare monitoring applications and a vision for transforming sensor data into real-time clinical feedback,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:01:19.104289Z

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This paper cites A survey on federated learning for resource-constrained iot devices,.

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications A survey on federated learning for resource-constrained iot devices,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:01:19.073626Z

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This paper cites Fedscr: Structure-based communi- cation reduction for federated learning,.

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications Fedscr: Structure-based communi- cation reduction for federated learning,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:01:19.052817Z

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This paper cites Fast federated learning by balancing communication trade-offs,.

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications Fast federated learning by balancing communication trade-offs,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:01:19.022400Z

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This paper cites Toward communication-learning trade- off for federated learning at the network edge,.

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications Toward communication-learning trade- off for federated learning at the network edge,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:01:18.991135Z

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Observation cf798698-16fa-4631-a9c2-6e318c3c4e1d · outbound

This paper cites FedMetaMed: Federated Meta-Learning for Personalized Medication in Distributed Healthcare Systems.

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications FedMetaMed: Federated Meta-Learning for Personalized Medication in Distributed Healthcare Systems

Reference 33

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This paper cites Fed-LDR: Federated Local Data-infused Graph Creation with Node-centric Model Refinement.

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications Fed-LDR: Federated Local Data-infused Graph Creation with Node-centric Model Refinement

Reference 34

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This paper cites Client scheduling and resource management for efficient training in heterogeneous iot-edge federated learning,.

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications Client scheduling and resource management for efficient training in heterogeneous iot-edge federated learning,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:01:18.924062Z

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This paper cites Federated learning with hierarchical clustering of local updates to improve training on non-iid data,.

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications Federated learning with hierarchical clustering of local updates to improve training on non-iid data,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:01:18.889706Z

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This paper cites Towards fast and accurate federated learning with non-iid data for cloud- based iot applications,.

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications Towards fast and accurate federated learning with non-iid data for cloud- based iot applications,

Reference 37

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This paper cites Deconstructing lottery tickets: Zeros, signs, and the supermask,.

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications Deconstructing lottery tickets: Zeros, signs, and the supermask,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:01:18.861813Z

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Observation 7bc51c11-a1b4-438a-833d-eb2c91ca58f2 · outbound

This paper cites Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation.

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation

Reference 39

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H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications Bayesian signsgd optimizer for federated learning,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:01:18.831902Z

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Observation 321015d4-1b85-4995-abb8-ba65c4473c8b · outbound

This paper cites Activity recog- nition from accelerometer data,.

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications Activity recog- nition from accelerometer data,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:01:18.797508Z

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Observation 51b5bda4-90ed-48b0-be4c-7f94055054e6 · outbound

This paper cites Transition-aware human activity recognition using smartphones,.

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications Transition-aware human activity recognition using smartphones,

Reference 42

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This paper cites Human activity recognition with smart- phone sensors using deep learning neural networks,.

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications Human activity recognition with smart- phone sensors using deep learning neural networks,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:01:18.730877Z

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Observation 938f4c03-96d8-43a7-9149-9685eb617517 · outbound

This paper cites Evaluation of the efficacy of iot deployment on petro-retail operations,.

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications Evaluation of the efficacy of iot deployment on petro-retail operations,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:01:18.698076Z

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