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Paper Citation Record · LEDGER

Decentralized Federated Learning by Partial Message Exchange

As of 8 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 2026-08-08T06:32:00.761636+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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source=pdf_text observed=2026-08-02T19:44:11.263845Z digest=sha256:bbc90aca27d2b7c3966f4e50a47f8ce8ccb7fa82e6862c11e32ec74fbbdfa266

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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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:fd9a997e28e986a9ee49d8d457a39d7b5cc978c9923315970a408d78996e392c

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:b55cf2c5281c2dc984d6061027b5f2babddf20d8385ee0eb26c4e7b279b5cac9

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=sha256:84ade501cc223c299042ad3b615688baf22ddfb5d80d10e8f28d841a28798db8

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:e7960b8f5a8f8a7fd6a256865b48b10c5f94e9924684017902eee4e4614f630e

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:b0e4329ad9ee589a6d29b001015f657baec338b11659571d26eac80fcb93b238

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:a5d5786351dec311e78d25562460e9f0838579dee024ce367ad33dc08d0918cc

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=sha256:9edac131ad3c89ea7b7b9050d4b26d6ef532b5fe50be3cb452c5fb941f20a28f

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:c5a655834db8c667843426dc7346ba5933e0e647184c4f99db8db54a58d87f14

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=sha256:75d6a452552658b40233d8b11f6e484d853509509e0764469bed9a74b31461db

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=sha256:667d236c130ffce599baa2369e31a6ca43b4390cb86c1145fc08b8e87aa74ee0

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=sha256:5d6432004e468f696fe911b71aff2e19ed610a0de918b32d3c4f18ecf8f68140

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:dd1a1a02020fb31f0cd4bec7d213348c17914074f81ebcb72f9290da59022afb

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=sha256:57812fd00341b84eb3b2e8d87c8cf4c59871e224cbdd85518decbc9f892c2c7b

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=sha256:6a5c79899fe44f474a383e6dbba0ed36b481315833260ef86d7877899e4c7327

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:eae5e4c8ccaa69d2fa99a01be3bd9957561a5c6c3f4d24cf3522f86145bf8ad0

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=sha256:05405cdcd3759fc0062f4d7ba5b3fe14fb641b54625730e2e9f4ee90d621a6d9

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=sha256:4aaf11184e4071be43901f545022f415d793e7dc26f90421284078d76471e922

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=sha256:63f8e6799f83ab612f1f8478d6a58d84975255b83fbed3284702fec191ebf821

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=sha256:378fde9f2c5f12e5433f62b00aaa691f1b81452c1563b8297f8178ef53069843

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:a9396b17a68131693bfcc99b36acc5974b4bec6afb670ab5b7eb9fd38dd4dcf1

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=sha256:7621f9c8a59f2e33edcdebb92a93baf7eadaf3036590c8c64e1d097fb4f52b6c

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=sha256:4d35926f2026f36b381298692690d806ad0c3e404014fb5fc3992aaa1c5ef9dc

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=sha256:3b456d34164b90d34482a2921248f5fa05b441cdccaa8d3327ebc76906b10461

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=sha256:9188081a8721035db3c22cd9afeccdf29428b76e18157b7c5aa8ccef2a9e0fb1

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=sha256:02aac25ae603e1d41a8a59bca79f32f4757bcd20fc4b07069695966925ce1446

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:b4cf68980f5a2cd0bb364609e83434096c94e250af62e82b52a15bbb5e3507c8

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=sha256:52cd1f7c5c281653acdf84905e8674e598708cec7e7b6f95f6fcffd82b8f6651

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:befd51a04112837c0cb89ec2166f6168767c6c265de76f70c9428936dba2790d

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:d8c74be31d8e2d24ae52dd8ccc74ae1e7941f5402999808d9a86de0a3c644830

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:c78fa56064a4d211c301432c96a6274f5b6d0d1d0248b72464a52a3415b3d338

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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source=arxiv_source observed=2026-07-02T19:44:47.733008Z digest=sha256:5e5dc49a1328fc355e839acebe443bed999f2ae8774641e1e11fe6e3d3c51cd1