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Paper Citation Record · LEDGER

Decentralized Federated Learning by Partial Message Exchange

As of 14 August 2026, this Paper Citation Record lists 66 of 66 outbound references and 1 inbound Pith citation observation for arXiv:2603.01730.

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

pith.paper-citation-record.v1
2603.01730 v3

Coverage vector

measured 66 of 66 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T19:44:17.278048Z

measured 67 of 67 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-02T19:44:47.733008Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T19:47:18.784816Z

Reference resolution

66 of 66 outbound references displayed

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External citation measurements

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Outbound references

Observation e317d730-dc85-47cb-841a-0fe3c19d3b64 · outbound

This paper cites Decentralized federated learning: Fundamentals, state of the art, frameworks, trends, and challenges,.

Decentralized Federated Learning by Partial Message Exchange Decentralized federated learning: Fundamentals, state of the art, frameworks, trends, and challenges,

Reference 1

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Observation d71a689e-aff2-4d24-bcc8-d6e3c8b7345f · outbound

This paper cites Decentralized federated learning: A survey on security and privacy,.

Decentralized Federated Learning by Partial Message Exchange Decentralized federated learning: A survey on security and privacy,

Reference 2

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Observation 846bf843-a398-472e-8358-930fa7aefe99 · outbound

This paper cites An innovative decentralized and distributed deep learning framework for predictive maintenance in the industrial internet of things,.

Decentralized Federated Learning by Partial Message Exchange An innovative decentralized and distributed deep learning framework for predictive maintenance in the industrial internet of things,

Reference 3

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Observation fe432c74-6201-4022-acb9-aa52cc109df4 · outbound

This paper cites Decentralized navigation with heterogeneous federated reinforcement learning for uav- enabled mobile edge computing,.

Decentralized Federated Learning by Partial Message Exchange Decentralized navigation with heterogeneous federated reinforcement learning for uav- enabled mobile edge computing,

Reference 4

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Observation 0e5faf2f-83d2-4131-b6d0-09b93103bebe · outbound

This paper cites Federated learning-based energy fore- casting and trading platform for decentralized renewable energy markets,.

Decentralized Federated Learning by Partial Message Exchange Federated learning-based energy fore- casting and trading platform for decentralized renewable energy markets,

Reference 5

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Observation c41525aa-662b-4921-b44e-44d14ba71d19 · outbound

This paper cites Federated learning meets blockchain in decentralized data sharing: Healthcare use case,.

Decentralized Federated Learning by Partial Message Exchange Federated learning meets blockchain in decentralized data sharing: Healthcare use case,

Reference 6

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Observation fbd0efca-23d6-404c-8f07-2b387cdb5bda · outbound

This paper cites Can decentralized algorithms outperform centralized algorithms? a case study for decentralized parallel stochastic gradient descent,.

Decentralized Federated Learning by Partial Message Exchange Can decentralized algorithms outperform centralized algorithms? a case study for decentralized parallel stochastic gradient descent,

Reference 7

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Observation 5afbc594-5f1c-4494-a792-78ee9a64692c · outbound

This paper cites Improving the model consistency of decentral- ized federated learning,.

Decentralized Federated Learning by Partial Message Exchange Improving the model consistency of decentral- ized federated learning,

Reference 8

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Observation 4340a924-59b7-48cb-9f29-d33f2b678e88 · outbound

This paper cites Topology-aware generalization of decentralized sgd,.

Decentralized Federated Learning by Partial Message Exchange Topology-aware generalization of decentralized sgd,

Reference 9

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Observation 227b8c1e-1bfd-4142-bfd2-122873bfe284 · outbound

This paper cites Decentralized optimiza- tion with edge sampling,.

Decentralized Federated Learning by Partial Message Exchange Decentralized optimiza- tion with edge sampling,

Reference 10

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Observation 2e081d8a-c13e-4aef-ab90-a36f6f9d27d1 · outbound

This paper cites De V os, S.

Decentralized Federated Learning by Partial Message Exchange De V os, S

Reference 11

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Observation a2e9a098-82b5-4599-b2a1-21dfed5009a8 · outbound

This paper cites Smart Sampling: Helping from Friendly Neighbors for Decentralized Federated Learning.

Decentralized Federated Learning by Partial Message Exchange Smart Sampling: Helping from Friendly Neighbors for Decentralized Federated Learning

Reference 12

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Observation fee3b85f-ee23-447a-815b-6590546d16d8 · outbound

This paper cites Personalized decentralized federated learning: A privacy-enhanced and byzantine-resilient approach,.

Decentralized Federated Learning by Partial Message Exchange Personalized decentralized federated learning: A privacy-enhanced and byzantine-resilient approach,

Reference 13

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Observation 44bd6a92-fbe4-4ea5-bf9c-a895109d4180 · outbound

This paper cites Distributed subgradient methods for multi-agent optimization,.

Decentralized Federated Learning by Partial Message Exchange Distributed subgradient methods for multi-agent optimization,

Reference 14

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Observation 0e93380b-2867-4772-9116-ce1d12c661e4 · outbound

This paper cites Com- munication compression for decentralized training,.

Decentralized Federated Learning by Partial Message Exchange Com- munication compression for decentralized training,

Reference 15

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Observation bb35fc2b-7b3d-4503-9044-00456717a207 · outbound

This paper cites The convergence of spar- sified gradient methods,.

Decentralized Federated Learning by Partial Message Exchange The convergence of spar- sified gradient methods,

Reference 16

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Observation d0132d68-9777-418b-82e1-a64869dcbf85 · outbound

This paper cites Sparse decen- tralized federated learning,.

Decentralized Federated Learning by Partial Message Exchange Sparse decen- tralized federated learning,

Reference 17

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Observation acf84ca3-5627-4c76-9cda-a39fb841289d · outbound

This paper cites Decentralized learning with unreliable communications,.

Decentralized Federated Learning by Partial Message Exchange Decentralized learning with unreliable communications,

Reference 18

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Observation 64a6e3d2-31c4-489c-ab82-eb5f8165e58d · outbound

This paper cites Decentralized multi-client functional encryption for in- ner product with applications to federated learning,.

Decentralized Federated Learning by Partial Message Exchange Decentralized multi-client functional encryption for in- ner product with applications to federated learning,

Reference 19

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Observation fdd04d28-4fd7-4aa0-9f0f-44883eafd0f3 · outbound

This paper cites Securing decentral- ized federated learning: cryptographic mechanisms for privacy and trust,.

Decentralized Federated Learning by Partial Message Exchange Securing decentral- ized federated learning: cryptographic mechanisms for privacy and trust,

Reference 20

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Observation f7110104-433c-413b-943b-967118060ac2 · outbound

This paper cites Decentralized nonconvex opti- mization with guaranteed privacy and accuracy,.

Decentralized Federated Learning by Partial Message Exchange Decentralized nonconvex opti- mization with guaranteed privacy and accuracy,

Reference 21

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Observation 361f2988-14a1-4e58-b86d-94eba9ee8427 · outbound

This paper cites Differentially private linearized admm algorithm for decentralized nonconvex optimization,.

Decentralized Federated Learning by Partial Message Exchange Differentially private linearized admm algorithm for decentralized nonconvex optimization,

Reference 22

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Observation 2624b4ed-b919-431a-9a7c-f327a7a81cf0 · outbound

This paper cites Dp-norm: Differential privacy primal-dual algorithm for decen- tralized federated learning,.

Decentralized Federated Learning by Partial Message Exchange Dp-norm: Differential privacy primal-dual algorithm for decen- tralized federated learning,

Reference 23

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Observation 94778d74-2ee5-44a6-bf90-13a622de9f44 · outbound

This paper cites Federated learning via inexact admm,.

Decentralized Federated Learning by Partial Message Exchange Federated learning via inexact admm,

Reference 24

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Observation f6440328-ffe3-4b4d-a2f3-7e31e97b0808 · outbound

This paper cites Decentralized federated averaging,.

Decentralized Federated Learning by Partial Message Exchange Decentralized federated averaging,

Reference 25

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Observation 98a6c711-a798-49b2-b074-1d4300390a66 · outbound

This paper cites Decentralized feder- ated learning: Balancing communication and computing costs,.

Decentralized Federated Learning by Partial Message Exchange Decentralized feder- ated learning: Balancing communication and computing costs,

Reference 26

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Observation 29c7e558-67e5-4842-aaec-f5c8fab44104 · outbound

This paper cites De- centralized deep learning with arbitrary communication compression,.

Decentralized Federated Learning by Partial Message Exchange De- centralized deep learning with arbitrary communication compression,

Reference 27

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source=pdf_text observed=2026-08-02T19:44:12.844298Z digest=sha256:3d4e629e6ae0ffea304e7c9ea46c4d44d7fea9e250e9dd6e6b17c57a49b2b585

Observation 304b8965-43b8-477c-af3c-49e83ecf9e61 · outbound

This paper cites Squarm- sgd: Communication-efficient momentum sgd for decen- tralized optimization,.

Decentralized Federated Learning by Partial Message Exchange Squarm- sgd: Communication-efficient momentum sgd for decen- tralized optimization,

Reference 28

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Observation 71222f06-90fd-4d96-8520-34721017bb3c · outbound

This paper cites Beer: Fasto(1/t)rate for decentralized nonconvex optimiza- tion with communication compression,.

Decentralized Federated Learning by Partial Message Exchange Beer: Fasto(1/t)rate for decentralized nonconvex optimiza- tion with communication compression,

Reference 29

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Observation 1110c756-9885-449c-b1b5-d39b9bfbdcc0 · outbound

This paper cites Decentralized sum-of- nonconvex optimization,.

Decentralized Federated Learning by Partial Message Exchange Decentralized sum-of- nonconvex optimization,

Reference 30

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Observation eabae8b9-e2db-4274-a8c3-87c50490e754 · outbound

This paper cites A decentralized proximal- gradient method with network independent step-sizes and separated convergence rates,.

Decentralized Federated Learning by Partial Message Exchange A decentralized proximal- gradient method with network independent step-sizes and separated convergence rates,

Reference 31

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Observation 39ba6f39-08df-4b37-9c3b-65a2e18d5935 · outbound

This paper cites Finite-bit quantization for distributed algorithms with linear con- vergence,.

Decentralized Federated Learning by Partial Message Exchange Finite-bit quantization for distributed algorithms with linear con- vergence,

Reference 32

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Observation 63a44a53-a2f4-402d-b4a5-c714b2c35988 · outbound

This paper cites Private and communication-efficient edge learning: A sparse differ- ential gaussian-masking distributed sgd approach,.

Decentralized Federated Learning by Partial Message Exchange Private and communication-efficient edge learning: A sparse differ- ential gaussian-masking distributed sgd approach,

Reference 33

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Observation 1c5b90d1-6125-426d-832f-6aaad24d8921 · outbound

This paper cites Federated learning with sparsified model perturbation: Improving accuracy under client-level differential privacy,.

Decentralized Federated Learning by Partial Message Exchange Federated learning with sparsified model perturbation: Improving accuracy under client-level differential privacy,

Reference 34

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Observation f72c6d89-e6d7-4d8a-9583-1990487e4095 · outbound

This paper cites Communication-Efficient Secure Aggregation in Decentralized Learning.

Decentralized Federated Learning by Partial Message Exchange Communication-Efficient Secure Aggregation in Decentralized Learning

Reference 35

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Observation 319a436d-7a04-4b57-95df-b5b192e12852 · outbound

This paper cites Numerical optimization,.

Decentralized Federated Learning by Partial Message Exchange Numerical optimization,

Reference 36

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source=pdf_text observed=2026-08-02T19:44:13.571358Z digest=sha256:27e4c7835142a78555da07c6e36eb5e2d9867db8c0e610928190b2d1ab9374f0

Observation 5344d6cd-06ea-42b2-b472-d010634e1085 · outbound

This paper cites Asynchronous Stochastic Gradient Descent with Delay Compensation.

Decentralized Federated Learning by Partial Message Exchange Asynchronous Stochastic Gradient Descent with Delay Compensation

Reference 37

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source=pdf_text observed=2026-08-02T19:44:13.735205Z digest=sha256:f2b778559ed4cec84c86036a311dd97e1caab9c4e6c6d61595cda1afb4ed7340

Observation 60d1e45d-4a15-4326-8bba-459faee91731 · outbound

This paper cites Parallel restarted sgd with faster convergence and less communication: Demystify- ing why model averaging works for deep learning,.

Decentralized Federated Learning by Partial Message Exchange Parallel restarted sgd with faster convergence and less communication: Demystify- ing why model averaging works for deep learning,

Reference 38

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source=pdf_text observed=2026-08-02T19:44:13.864880Z digest=sha256:e1a162cf12df612fba1a2fbcfe51b2878d681f269d05f152a68af20e230fa2b1

Observation e40e6986-627a-4445-9258-6a7db098ba00 · outbound

This paper cites Cooperative sgd: A unified framework for the design and analysis of local-update sgd algorithms,.

Decentralized Federated Learning by Partial Message Exchange Cooperative sgd: A unified framework for the design and analysis of local-update sgd algorithms,

Reference 39

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source=pdf_text observed=2026-08-02T19:44:14.060519Z digest=sha256:38369f88dea4fd2748da7364986ad6a669d8269e2214272d27ea2a2ef153ccad

Observation ee6d1cc0-115e-4293-856f-55720fcfaa93 · outbound

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

Decentralized Federated Learning by Partial Message Exchange Communication-efficient learning of deep networks from decentralized data,

Reference 40

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source=pdf_text observed=2026-08-02T19:44:14.181024Z digest=sha256:cf3af87843206780cd75000c9ac84b5e8ec2eff4d93c3a39f55aea5487f03f28

Observation ad3bd8f1-5e8d-41e9-9ed5-6780b3adddfd · outbound

This paper cites On the Convergence of FedAvg on Non-IID Data.

Decentralized Federated Learning by Partial Message Exchange On the Convergence of FedAvg on Non-IID Data

Reference 41

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source=pdf_text observed=2026-08-02T19:44:14.314881Z digest=sha256:7cb319efa734fde92fdc363e68c97de4b1ab1e22021b6e16e56035c8c2916610

Observation 800f2dfe-690f-4e0e-a2a9-bd5b74ed2c30 · outbound

This paper cites Federated optimization in heterogeneous networks,.

Decentralized Federated Learning by Partial Message Exchange Federated optimization in heterogeneous networks,

Reference 42

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source=pdf_text observed=2026-08-02T19:44:14.432735Z digest=sha256:52ab1b10b29523d2d44eaf75e9a828562bc7fb14e8bd73b5d8f75cbca960b78b

Observation 70d04a0f-a8d4-47b3-8d2d-bf9b23b43ecf · outbound

This paper cites Fedgia: An efficient hybrid algorithm for federated learning,.

Decentralized Federated Learning by Partial Message Exchange Fedgia: An efficient hybrid algorithm for federated learning,

Reference 43

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source=pdf_text observed=2026-08-02T19:44:14.561578Z digest=sha256:018d9e93619bbb724398eb1878887dd1f5c40f2472035a7f2b3853e2bc8a5c96

Observation cf4f2841-1ac9-411e-80cf-ab2156e68a21 · outbound

This paper cites The sparse vector technique, revisited,.

Decentralized Federated Learning by Partial Message Exchange The sparse vector technique, revisited,

Reference 44

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source=pdf_text observed=2026-08-02T19:44:14.697937Z digest=sha256:75b71bfcd630954beaa3de5f565ca1469dc650742f5058623f33faf9d8f14aef

Observation 294daf0e-c19b-48c9-a71c-5d2c865687bc · outbound

This paper cites Improving sparse vector tech- nique with renyi differential privacy,.

Decentralized Federated Learning by Partial Message Exchange Improving sparse vector tech- nique with renyi differential privacy,

Reference 45

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source=pdf_text observed=2026-08-02T19:44:14.814181Z digest=sha256:d6b88a83307f01934687f75e364f1b216b6c08c1b905bc72b3b52dec009ca008

Observation a6c94fa2-8306-4b37-90a6-1247c5842f47 · outbound

This paper cites Secure federated averaging algorithm with differential privacy,.

Decentralized Federated Learning by Partial Message Exchange Secure federated averaging algorithm with differential privacy,

Reference 46

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source=pdf_text observed=2026-08-02T19:44:15.008735Z digest=sha256:b8630514d0ffbd5ceaf56e518e60d4559e0e705874fde582306e82829438dc60

Observation ad5e005d-8525-446e-b767-a0ba58e55ab3 · outbound

This paper cites Federated Stochastic Primal-dual Learning with Differential Privacy.

Decentralized Federated Learning by Partial Message Exchange Federated Stochastic Primal-dual Learning with Differential Privacy

Reference 47

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source=pdf_text observed=2026-08-02T19:44:15.177413Z digest=sha256:f3051fe2f09437111d11fb5a7c1a5b43a8c7ba2b48b65c66c8ba2eabb888f248

Observation c89e36ad-1808-4ff5-8bdc-0fca144ac977 · outbound

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

Decentralized Federated Learning by Partial Message Exchange Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

Reference 48

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source=pdf_text observed=2026-08-02T19:44:15.320107Z digest=sha256:467a6934508a976368f456c03857551b1c085c7ebe4b28f9dc49bdcbf83dd1c8

Observation ff3b4b19-4113-4434-9224-e135f745f058 · outbound

This paper cites Deep residual learning for image recognition,.

Decentralized Federated Learning by Partial Message Exchange Deep residual learning for image recognition,

Reference 49

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source=pdf_text observed=2026-08-02T19:44:15.488134Z digest=sha256:cc37dd2515b06c23f03b5f228335fbc002e686d9e01fdb549a02623cf982d73d

Observation b02239fb-fa11-4900-b9e3-d2cc7c8022b8 · outbound

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

Decentralized Federated Learning by Partial Message Exchange Learning multiple layers of features from tiny images,

Reference 50

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source=pdf_text observed=2026-08-02T19:44:15.635415Z digest=sha256:183056516adb343828f87b853f72c1d4acaee75d5a5de4624d83d71c69e73309

Observation 55366b6d-5c09-4016-84ce-af9eeb8c26bc · outbound

This paper cites This is adopted for analytical convenience without loss of generality.

Decentralized Federated Learning by Partial Message Exchange This is adopted for analytical convenience without loss of generality

Reference 51

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source=pdf_text observed=2026-08-02T19:44:15.736620Z digest=sha256:d7599ca8dc2473172f142e1e3173ee2327748d1f923c856c2e6528a5d47b4eea

Observation ab17072d-bd76-40af-adf2-821e5fa38ca6 · outbound

This paper cites That is, at every iteration, nodeiselects the same number of neighbor nodes to join in the training.

Decentralized Federated Learning by Partial Message Exchange That is, at every iteration, nodeiselects the same number of neighbor nodes to join in the training

Reference 52

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source=pdf_text observed=2026-08-02T19:44:15.871601Z digest=sha256:8f56b818e27e481f38bf15d1af5236959dc69064d14fe54e49d5f2c357fc4686

Observation 9836d4c0-ad13-4844-b730-ec1807e673c8 · outbound

This paper cites Again, this is adopted for analytical convenience without loss of generality.

Decentralized Federated Learning by Partial Message Exchange Again, this is adopted for analytical convenience without loss of generality

Reference 53

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source=pdf_text observed=2026-08-02T19:44:15.989933Z digest=sha256:0013bfbdf8b2eecb1481c93a51c8d5a5a310633e7723a75ceab86aa03abfe77e

Observation 0dcc4eff-5f34-4424-a07a-931750f19c7c · outbound

This paper cites wk iℓ − 1 r X j∈N k i,ℓ wk jℓ !2 λk i,ℓ =r # +P(λ k i,ℓ = 0)E h (wk iℓ −w k iℓ)2 λk i,ℓ = 0 i = tiX r=1 P(λk i,ℓ =r)E.

Decentralized Federated Learning by Partial Message Exchange wk iℓ − 1 r X j∈N k i,ℓ wk jℓ !2 λk i,ℓ =r # +P(λ k i,ℓ = 0)E h (wk iℓ −w k iℓ)2 λk i,ℓ = 0 i = tiX r=1 P(λk i,ℓ =r)E

Reference 54

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source=pdf_text observed=2026-08-02T19:44:16.158492Z digest=sha256:079ca8a6ece2ff73caa5088fdce0461f567bac6b9964c8c164810be40756dd5e

Observation 1ec003d7-8810-4f7e-99be-5438e2d79fc0 · outbound

This paper cites an unresolved cited work.

Decentralized Federated Learning by Partial Message Exchange Unresolved cited work

Reference 55

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source=pdf_text observed=2026-08-02T19:44:16.307389Z digest=sha256:92a0388998790f4b306a90a10d3b896d056f09d3a1180c1e0453ce714232fe5e

Observation 69fd5488-e515-4f53-94e7-6e9c881531b6 · outbound

This paper cites Proof.Since 1) has been shown in Lemma 3, we only prove 2).

Decentralized Federated Learning by Partial Message Exchange Proof.Since 1) has been shown in Lemma 3, we only prove 2)

Reference 56

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Observation 4002e7f2-c091-41a9-b914-653aeccc28ff · outbound

This paper cites an unresolved cited work.

Decentralized Federated Learning by Partial Message Exchange Unresolved cited work

Reference 57

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source=pdf_text observed=2026-08-02T19:44:16.583610Z digest=sha256:32e69925990cef82ff3192d6f2c8073c2e47d335263000eb0ca2cd26b03f66f0

Observation d2728ad6-2197-451f-8e24-ab5edc567075 · outbound

This paper cites an unresolved cited work.

Decentralized Federated Learning by Partial Message Exchange Unresolved cited work

Reference 58

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source=pdf_text observed=2026-08-02T19:44:16.671674Z digest=sha256:dbbf0b93820ac42a4a2c98efcbf980bccab42f2508ce698e0e60e7546522f08d

Observation a8fd5d4a-8a5f-4608-96dd-0ac4df236f9e · outbound

This paper cites Proof.1) By the triangle inequality and Cauchy-Schwarz: ∥Ewk+1 −Ew k∥ ≤E∥wk+1 −w k∥ ≤ q E∥wk+1 −w k∥2 ≤ c γk/2.

Decentralized Federated Learning by Partial Message Exchange Proof.1) By the triangle inequality and Cauchy-Schwarz: ∥Ewk+1 −Ew k∥ ≤E∥wk+1 −w k∥ ≤ q E∥wk+1 −w k∥2 ≤ c γk/2

Reference 59

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source=pdf_text observed=2026-08-02T19:44:16.752234Z digest=sha256:a38875ace48d7d67ea72fc878ad8cff7c009e761c01c4789941e3ca4cc85d045

Observation 1c0c8556-5887-4ea9-b2c0-f5e879c438f7 · outbound

This paper cites This implies that there is a constantc >0such that |f(w k)−f(w ∞)| ≤c∥wk −w ∞∥.

Decentralized Federated Learning by Partial Message Exchange This implies that there is a constantc >0such that |f(w k)−f(w ∞)| ≤c∥wk −w ∞∥

Reference 60

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source=pdf_text observed=2026-08-02T19:44:16.836477Z digest=sha256:f4e170891bc622c1aae9b20eb3c057d657128c23154ca90baa898ded96e3d740

Observation a97cb2a7-caa5-4d6d-a14e-a5f0f747549f · outbound

This paper cites We first showlim N→∞ ∆N = 0.

Decentralized Federated Learning by Partial Message Exchange We first showlim N→∞ ∆N = 0

Reference 61

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source=pdf_text observed=2026-08-02T19:44:16.918147Z digest=sha256:cba2a59d411c213ac4805c601f2b5e36ac8e10fa87109a306ac362f98c62f8b5

Observation c65d6cd7-3f14-4568-bd50-8f784f7286f5 · outbound

This paper cites an unresolved cited work.

Decentralized Federated Learning by Partial Message Exchange Unresolved cited work

Reference 62

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source=pdf_text observed=2026-08-02T19:44:17.031119Z digest=sha256:39f3e4d989c0382411bc0437d2e51b6c38d1652e93cef03e1454c69a45abf5e2

Observation 1ef97ead-80c7-46f7-badd-350516c3e562 · outbound

This paper cites an unresolved cited work.

Decentralized Federated Learning by Partial Message Exchange Unresolved cited work

Reference 63

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source=pdf_text observed=2026-08-02T19:44:17.093131Z digest=sha256:93b9ba6ab054a9b2f785f2a8a8dd2a94ec0bf43e74c3626c0f3a81205517347d

Observation d9180cca-c463-4718-9698-2c356009f791 · outbound

This paper cites Proof.1) From (75) and (74), sequence{ eH k}is non-increasing and bounded from below.

Decentralized Federated Learning by Partial Message Exchange Proof.1) From (75) and (74), sequence{ eH k}is non-increasing and bounded from below

Reference 64

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source=pdf_text observed=2026-08-02T19:44:17.148277Z digest=sha256:0d3d982fda1ec579a8c7c53490c7a205ac4b23a3e869228f21b41c7d155c12b9

Observation 24b0aa7e-2471-494c-a7c4-de3a5518fa6a · outbound

This paper cites It is easy to checkϖ k ∈N(2δ) for allk≥0.

Decentralized Federated Learning by Partial Message Exchange It is easy to checkϖ k ∈N(2δ) for allk≥0

Reference 65

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source=pdf_text observed=2026-08-02T19:44:17.216349Z digest=sha256:ed16f8739645d1199cb8b10a6b50ea0c1db1d5ea828c811f7d26c443e85b3dd5

Observation 88ae75f1-27bf-4814-bcb2-18ed97f10658 · outbound

This paper cites an unresolved cited work.

Decentralized Federated Learning by Partial Message Exchange Unresolved cited work

Reference 66

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source=pdf_text observed=2026-08-02T19:44:17.278048Z digest=sha256:cebaeddc2be8bab40b0c23b848bcf2b0bbd58fd0a13405dd5d72cd3d32b0af6a

Pith citing papers

Observation 42b2c74a-bae9-4e82-bb26-2bd2f91b8fa4 · inbound

TallyTrain: Communication-Efficient Federated Distillation cites this paper.

TallyTrain: Communication-Efficient Federated Distillation Decentralized Federated Learning by Partial Message Exchange

Reference 13

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arxiv_id, observed 2026-07-07T03:18:54.296089Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-07-02T19:44:47.733008Z digest=sha256:b0efc9e8b0a1af107b228acabac45487026f878e96daa73bae387b1a56be1851