Paper Citation Record · LEDGER

Differentially Private Federated Clustering with Random Rebalancing

As of 8 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2508.06183.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2508.06183 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T23:09:55.310137Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

40 of 40 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b9245a1b-5007-4f61-91ca-448cfdfd588a · outbound

This paper cites URL https://www.

Differentially Private Federated Clustering with Random Rebalancing URL https://www

Reference 1

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Observation 4ba84830-9481-4d2c-aa06-d4c2dff28cc0 · outbound

This paper cites Federated Learning with Personalization Layers.

Differentially Private Federated Clustering with Random Rebalancing Federated Learning with Personalization Layers

Reference 2

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Source-reported events for the cited work

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Observation 466eae97-9f75-4afa-8bc5-489b62ff8a3b · outbound

This paper cites Dcfl: Dynamic clustered federated learning under differential privacy settings.

Differentially Private Federated Clustering with Random Rebalancing Dcfl: Dynamic clustered federated learning under differential privacy settings

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:09:55.705894Z

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Observation d115d313-1cbc-41d0-bb67-96cac98e23f7 · outbound

This paper cites Dif- ferentially private clustering in high-dimensional euclidean spaces.

Differentially Private Federated Clustering with Random Rebalancing Dif- ferentially private clustering in high-dimensional euclidean spaces

Reference 4

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Observation b5c97601-afd5-461a-a710-9d4926db74f7 · outbound

This paper cites LEAF: A Benchmark for Federated Settings.

Differentially Private Federated Clustering with Random Rebalancing LEAF: A Benchmark for Federated Settings

Reference 5

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Observation ef8bb8e5-994e-4930-b461-d6607c169a4d · outbound

This paper cites Locally private k-means in one round.

Differentially Private Federated Clustering with Random Rebalancing Locally private k-means in one round

Reference 6

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Observation e860b9c9-b481-40fc-98e0-ed8664abad7b · outbound

This paper cites Emnist: Extending mnist to handwritten letters.

Differentially Private Federated Clustering with Random Rebalancing Emnist: Extending mnist to handwritten letters

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:09:55.676686Z

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Observation 445e8b64-3ab5-42d1-9a77-0bffecb24441 · outbound

This paper cites Scalable differentially private clustering via hierarchically separated trees.

Differentially Private Federated Clustering with Random Rebalancing Scalable differentially private clustering via hierarchically separated trees

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:09:55.667232Z

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Observation d817f924-d26e-4d06-b3d7-f050547f46f7 · outbound

This paper cites Heterogeneity for the win: One-shot federated clustering.

Differentially Private Federated Clustering with Random Rebalancing Heterogeneity for the win: One-shot federated clustering

Reference 9

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Observation 5309ed36-7e52-492a-a1fd-78a7e05da10f · outbound

This paper cites Calibrating noise to sensitivity in private data analysis.

Differentially Private Federated Clustering with Random Rebalancing Calibrating noise to sensitivity in private data analysis

Reference 10

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Source-reported events for the cited work

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Observation a2ab0970-0ae0-4348-a930-b9fd5a4deaf0 · outbound

This paper cites An efficient framework for clustered federated learning.

Differentially Private Federated Clustering with Random Rebalancing An efficient framework for clustered federated learning

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:09:55.642639Z

Source-reported events for the cited work

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Observation 37970993-6d43-4d84-92fa-bd2bd6dab0e6 · outbound

This paper cites Clustered federated learning with adaptive local differential privacy on heterogeneous iot data.

Differentially Private Federated Clustering with Random Rebalancing Clustered federated learning with adaptive local differential privacy on heterogeneous iot data

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:09:55.633278Z

Source-reported events for the cited work

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Observation 922eac27-2a0e-42dd-b613-cdce637b509b · outbound

This paper cites Optimal differentially private algorithms for k-means clustering.

Differentially Private Federated Clustering with Random Rebalancing Optimal differentially private algorithms for k-means clustering

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:09:55.623569Z

Source-reported events for the cited work

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Observation b5c2ee3f-c1cf-465a-8a64-d0cd79c64533 · outbound

This paper cites Advances and open problems in federated learning.

Differentially Private Federated Clustering with Random Rebalancing Advances and open problems in federated learning

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:09:55.613931Z

Source-reported events for the cited work

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Observation 227db902-767b-4334-9008-d7062f00a056 · outbound

This paper cites Clustered federated learning via gradient- based partitioning.

Differentially Private Federated Clustering with Random Rebalancing Clustered federated learning via gradient- based partitioning

Reference 15

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Source-reported events for the cited work

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Observation 31fc49b5-ecb7-4359-a48a-ab622053ce8a · outbound

This paper cites Learning multiple layers of features from tiny images.

Differentially Private Federated Clustering with Random Rebalancing Learning multiple layers of features from tiny images

Reference 16

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Observation c4620340-fdf5-4b57-939d-6b0b6277819b · outbound

This paper cites Federated learning: Chal- lenges, methods, and future directions.

Differentially Private Federated Clustering with Random Rebalancing Federated learning: Chal- lenges, methods, and future directions

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:09:55.588708Z

Source-reported events for the cited work

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Observation a88d86fb-fbf5-4dbe-9831-be4dcbec4767 · outbound

This paper cites Private adaptive optimization with side information.

Differentially Private Federated Clustering with Random Rebalancing Private adaptive optimization with side information

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:09:55.579837Z

Source-reported events for the cited work

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Observation 0775e0bc-7f22-49f8-ac7e-a601565fce11 · outbound

This paper cites On the convergence of fedavg on non-iid data.

Differentially Private Federated Clustering with Random Rebalancing On the convergence of fedavg on non-iid data

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:09:55.570027Z

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Observation 9136ed1d-a6d2-4151-bbc7-40dc94714fd2 · outbound

This paper cites Differentially private federated clustering over non-iid data.

Differentially Private Federated Clustering with Random Rebalancing Differentially private federated clustering over non-iid data

Reference 20

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Observation 4a1b8ed6-dd9d-4009-8ece-e54593ca2d64 · outbound

This paper cites On privacy and personalization in cross-silo federated learning.

Differentially Private Federated Clustering with Random Rebalancing On privacy and personalization in cross-silo federated learning

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:09:55.550382Z

Source-reported events for the cited work

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Observation 3a21bb04-c22b-4cfe-889f-644dc6700013 · outbound

This paper cites Multi-center federated learning: clients clustering for better personalization.

Differentially Private Federated Clustering with Random Rebalancing Multi-center federated learning: clients clustering for better personalization

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:09:55.540387Z

Source-reported events for the cited work

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Observation 50e4aefb-980b-4584-99ef-6283abcd7491 · outbound

This paper cites Privacy- preserving clustering federated learning for non-iid data.

Differentially Private Federated Clustering with Random Rebalancing Privacy- preserving clustering federated learning for non-iid data

Reference 23

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Observation 7fdca323-db33-41b3-a1f3-a81d8cc43354 · outbound

This paper cites Structured federated learning through clustered additive modeling.

Differentially Private Federated Clustering with Random Rebalancing Structured federated learning through clustered additive modeling

Reference 24

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Observation 3bcbb074-1cac-4f11-8d10-9e24d052e1aa · outbound

This paper cites Differentially Private Clustered Federated Learning.

Differentially Private Federated Clustering with Random Rebalancing Differentially Private Clustered Federated Learning

Reference 25

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Observation fa4cfb7d-e976-439f-a16e-b88afb9d7fea · outbound

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

Differentially Private Federated Clustering with Random Rebalancing Communication-efficient learning of deep networks from decentralized data

Reference 26

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Observation 7da9e9b6-d762-4ee5-b7f5-ba11276e3956 · outbound

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

Differentially Private Federated Clustering with Random Rebalancing Communication-efficient learning of deep networks from decentralized data

Reference 27

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This paper cites Learning differentially private recurrent language models.

Differentially Private Federated Clustering with Random Rebalancing Learning differentially private recurrent language models

Reference 28

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Observation 1fc32c12-7cea-4af0-b6cb-f4c6f86c0a97 · outbound

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Differentially Private Federated Clustering with Random Rebalancing Rényi differential privacy

Reference 29

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Source-reported events for the cited work

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Observation 46b0e604-5772-4017-9984-526949809c12 · outbound

This paper cites Clustering algorithms for the centralized and local models.

Differentially Private Federated Clustering with Random Rebalancing Clustering algorithms for the centralized and local models

Reference 30

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Observation a0d31fd6-7066-4782-8b84-9a6639174984 · outbound

This paper cites The complete works of William Shakespeare.

Differentially Private Federated Clustering with Random Rebalancing The complete works of William Shakespeare

Reference 31

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Source-reported events for the cited work

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Observation 0c545f49-e29f-4d08-92a4-f4b49597488e · outbound

This paper cites Make landscape flatter in differentially private federated learning.

Differentially Private Federated Clustering with Random Rebalancing Make landscape flatter in differentially private federated learning

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:09:55.454612Z

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This paper cites Locally private k-means clustering.

Differentially Private Federated Clustering with Random Rebalancing Locally private k-means clustering

Reference 33

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Observation 399c03a3-1cf5-45bf-8974-e8e74411ec2b · outbound

This paper cites Subsampled rényi differential privacy and analytical moments accountant.

Differentially Private Federated Clustering with Random Rebalancing Subsampled rényi differential privacy and analytical moments accountant

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:09:55.434663Z

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Observation 93ea0c4f-c97d-44c0-a934-c209b2bfed50 · outbound

This paper cites Motley: Benchmarking Heterogeneity and Personalization in Federated Learning.

Differentially Private Federated Clustering with Random Rebalancing Motley: Benchmarking Heterogeneity and Personalization in Federated Learning

Reference 35

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This paper cites Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms.

Differentially Private Federated Clustering with Random Rebalancing Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

Reference 36

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Differentially Private Federated Clustering with Random Rebalancing Unresolved cited work

Reference 37

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Differentially Private Federated Clustering with Random Rebalancing Unresolved cited work

Reference 38

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Differentially Private Federated Clustering with Random Rebalancing Unresolved cited work

Reference 39

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Observation 0b2807be-653b-4561-a597-f2e672c82087 · outbound

This paper cites Balanced Clusters.

Differentially Private Federated Clustering with Random Rebalancing Balanced Clusters

Reference 40

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Source-reported events for the cited work

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Pith citing papers

No inbound Pith citation observations are available.