Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-15T21:32:44.863453Z
Paper Citation Record · LEDGER
As of 20 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 0 inbound Pith citation observations for arXiv:2505.09704.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-15T21:32:44.863453Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
54 of 54 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 547e373d-f2f9-4457-87b1-8d48af17bd71 · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods Trends in data centre energy consumption under the european code of conduct for data centre energy efficiency,
Reference 1
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 1a21c94b-b687-4152-909e-6557c495f58b · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods Green cloud computing: Balancing energy in processing, storage, and transport,
Reference 2
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 12c639ae-40b7-4b61-9abf-3aeb98e7cc57 · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods Estimating Energy Consumption of Cloud, Fog, and Edge Computing Infrastructures,
Reference 3
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation f55fa8a7-bb85-467c-90fb-f2f5ecc0501b · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods The Cost of Training Machine Learning Models over Distributed Data Sources,
Reference 4
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation f861f3ba-a828-4d5a-b7c7-392dc59b1806 · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods Federated Learning With Co- operating Devices: A Consensus Approach for Massive IoT Networks,
Reference 5
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 1c38cbb0-1491-4b0c-aa3a-c5f7e2436912 · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods Learning- Based Computation Offloading for IoT Devices With Energy Harvest- ing,
Reference 6
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 703a9193-e647-47a0-9058-ef97c60aab7c · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods Energy-Efficient Artificial Intelligence of Things With Intelligent Edge,
Reference 7
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 1169a79b-f727-4fd0-88e7-c48ee18e87c0 · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods A Survey on Federated Learning for Resource-Constrained IoT Devices,
Reference 8
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 2d9e42ed-3af8-44ed-ada9-9c49d0e77ee9 · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods A Survey on Federated Learning: The Journey From Centralized to Distributed On-Site Learning and Beyond,
Reference 9
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 8b1dce76-c050-423f-a6d8-4182ff8f31a7 · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods Towards Federated Learning at Scale: System Design,
Reference 10
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation f0ae38c6-0e85-4216-bbf6-c452934cc0ff · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods On the Convergence of FedAvg on Non-IID Data,
Reference 11
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8c59b98c-a50e-440e-a1e7-30234bcf250e · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods Federated Learning With Non-IID Data: A Survey,
Reference 12
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation ff935fed-ff14-4f1a-a941-57e8af35e7c8 · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods Federated Optimization in Heterogeneous Networks,
Reference 13
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f3f55d12-6b55-4100-8522-f0c474a17694 · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods Client Selection in Federated Learning: Convergence Analysis and Power-of-Choice Selection Strategies
Reference 14
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5906e0c9-8d29-43aa-80dc-f74354297693 · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods Optimal Client Sampling for Federated Learning
Reference 15
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 47d4836b-06cf-479d-be29-8e184a22c3a3 · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods FedCor: Correlation-Based Active Client Selection Strategy for Het- erogeneous Federated Learning,
Reference 16
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation bafd248d-468a-4272-9db2-015d02252da5 · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods Delta: Diverse client sam- pling for fasting federated learning,
Reference 17
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation b7306199-a003-4c89-b7d7-c02d16b62172 · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods Clustered Sampling: Low-Variance and Improved Representativity for Clients Selection in Federated Learning,
Reference 18
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 1b053b45-f1c4-4f9b-8924-9c354ea329a8 · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods Diverse client selection for federated learning via submodular max- imization,
Reference 19
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c483594b-4d48-4333-9bc5-1b2e261497fc · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods Fast heterogeneous federated learning with hybrid client selection,
Reference 20
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation fae85d4c-2738-42e5-bf5e-076a85799aff · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods FLIS: Clustered Fed- erated Learning Via Inference Similarity for Non-IID Data Distribution ,
Reference 21
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 035adfaf-ce28-48fc-ab9f-02e0cc07468f · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods No Fear of Heterogeneity: Classifier Calibration for Federated Learning with Non- IID Data,
Reference 22
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 44e67a8e-cf52-4522-a546-c13124ccbe59 · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods Fedcorr: Multi- stage federated learning for label noise correction,
Reference 23
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 19697463-d50b-4cfe-8f1c-422c3890d3b0 · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods Learn from Others and Be Yourself in Heterogeneous Federated Learning,
Reference 24
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 38425559-51ee-4d07-876d-cd4a6067a2fd · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods CIFAR-10 (Canadian Institute for Advanced Research)
Reference 25
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 9cc2439a-c7c8-4179-9945-318c036ebb5a · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods Energy Efficient Federated Learning Over Wireless Communication Networks,
Reference 26
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation cd4f0301-e936-4d8b-9ab7-ea9916ac3ded · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods Fedgroup-prune: Iot device amicable and training-efficient federated learning via combined group lasso sparse model pruning,
Reference 27
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 4e794803-0203-41b3-b7bd-b8d0859ca91e · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods Feder- ated Learning Under Heterogeneous and Correlated Client Availability,
Reference 28
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 2af37693-1547-4824-9838-66bcd28e83c9 · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods Measuring Data Similarity for Efficient Federated Learning: A Feasibility Study ,
Reference 29
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 47b1cd74-0599-4e37-a2ef-15c807aa0328 · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods Advances and open problems in federated learning,
Reference 30
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6c4655c0-4a4a-4b75-aa57-024336e910f9 · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods Federated Learning on Non-IID Data Silos: An Experimental Study,
Reference 31
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation b62871c8-4869-4563-b976-ff3c8b2f5229 · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification
Reference 32
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation aa76aaf4-a6c7-40c2-8ac2-4b5bc0240245 · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods Communication-Efficient Distributionally Robust Decentralized Learning,
Reference 33
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 0c277c51-c3d3-4d7d-a52f-ab628345266e · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods A Joint Learning and Communications Framework for Federated Learning Over Wireless Networks,
Reference 34
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 095c3655-847d-4edb-8321-b82a637bb96b · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods Local SGD Converges Fast and Communicates Little,
Reference 35
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 44be7339-6a70-4c06-bad3-1736e8e503fb · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods Convergence time optimiza- tion for federated learning over wireless networks,
Reference 36
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 8bbad7bd-cdbc-471f-8a62-a3cad3dc8d5e · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods Optimal Client Sampling for Federated Learning,
Reference 37
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 59378d92-0ad8-4f95-bd8e-50863df4f4b1 · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods Neyman, On the Two Different Aspects of the Representative Method: the Method of Stratified Sampling and the Method of Purposive Selec- tion
Reference 38
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 690225b1-14a4-4cb3-a0d8-b43085356b42 · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods Repulsive clustering based pilot assignment for cell-free massive MIMO systems,
Reference 39
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation ee27d44f-14da-41c5-a2eb-52b8aebacb23 · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods Deep Repulsive Clustering of Ordered Data Based on Order-Identity Decomposition ,
Reference 40
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation c1a3d49e-1604-4dd0-b187-47d2fdd78a8b · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods Heuristic and special case algorithms for dispersion problems,
Reference 41
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 89af0f79-a229-4dfc-a80a-5729452bfdbf · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods Inferring class-label distribution in feder- ated learning,
Reference 42
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 225d9b0f-4681-45b6-bb1d-d37e7bf6f6d8 · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods Neural Collapse Inspired Feature-Classifier Alignment for Few-Shot Class-Incremental Learning,
Reference 43
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 2b4686ba-71ef-471f-a219-54441fcd2fe5 · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods mlco2/codecarbon: v2.4.1,
Reference 44
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 49665268-719d-4276-98cf-bc9910e34598 · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods Evaluating the carbon footprint of NLP methods: a survey and analysis of existing tools,
Reference 45
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 7e4ac5ab-01a5-4b93-8041-c9fd89b37dfa · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods How to estimate carbon footprint when training deep learning models? A guide and review,
Reference 46
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation c0cffb1b-5309-4bf4-91a1-107e55d6d861 · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods Evaluating the RAM energy consumption at the stage of software development,
Reference 47
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation a2468431-55d9-4bfc-9ec4-f8748f8d820a · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods IEEE 802.11 ax: High-efficiency WLANs,
Reference 48
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation d2b7a9f0-ee82-4e5a-9837-d7f7f5fd5eb9 · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms
Reference 49
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e4da9b61-9122-443f-b705-4afe35f3d924 · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods Differential privacy,
Reference 50
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4e1c7d0c-e60b-4fd9-af9b-249ee58c804d · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods The algorithmic foundations of differential privacy,
Reference 51
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a1c93bc4-298f-4389-b8a6-16c23f9b46af · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods Federated learning with differential privacy: Algorithms and performance analysis,
Reference 52
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 609ed780-528c-4c11-84a1-9241b8c1e564 · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods Federated learning with differential privacy: Algorithms and performance analysis,
Reference 53
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation a773aaa2-b677-4ec7-93d2-a42c4c0cc596 · outbound
Energy-Efficient Federated Learning for AIoT using Clustering Methods Available: https://doi.org/10.5281/zenodo.11171501
Reference 2024
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
No inbound Pith citation observations are available.