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Paper Citation Record · LEDGER

Accelerated Training of Federated Learning via Second-Order Methods

As of 17 August 2026, this Paper Citation Record lists 100 of 106 outbound references and 0 inbound Pith citation observations for arXiv:2505.23588.

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

pith.paper-citation-record.v1
2505.23588 v1

Coverage vector

measured 100 of 106 reference resolution

Typed states for the displayed outbound observations.

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measured 100 of 100 standing notices

One-hop event checks from named stored sources.

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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

100 of 106 outbound references displayed

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  • verified fuzzy41
  • unresolved57
  • parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7fab7cc0-541f-4cb5-8b81-c38f6b1e11f1 · outbound

This paper cites Communication-Efficient Learning of Deep Networks from Decentralized Data.

Accelerated Training of Federated Learning via Second-Order Methods Communication-Efficient Learning of Deep Networks from Decentralized Data

Reference 1

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Observation 772ec515-b0aa-47d4-b49f-91c7518ab075 · outbound

This paper cites Fedprox: Fedsplit algorithm based federated learning for statistical and system heterogeneity in medical data com- munication,.

Accelerated Training of Federated Learning via Second-Order Methods Fedprox: Fedsplit algorithm based federated learning for statistical and system heterogeneity in medical data com- munication,

Reference 2

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Observation 137447d9-85a6-4c4c-849a-448299e90378 · outbound

This paper cites SCAFFOLD: stochastic controlled averaging for federated learning,.

Accelerated Training of Federated Learning via Second-Order Methods SCAFFOLD: stochastic controlled averaging for federated learning,

Reference 3

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Observation c8d13219-cf0e-4ae7-b216-7594f4491c9e · outbound

This paper cites Model-contrastive federated learning,.

Accelerated Training of Federated Learning via Second-Order Methods Model-contrastive federated learning,

Reference 4

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Observation cf66b1b2-f313-467c-b006-99771aa64858 · outbound

This paper cites Federated learning based on dynamic regulariza- tion,.

Accelerated Training of Federated Learning via Second-Order Methods Federated learning based on dynamic regulariza- tion,

Reference 5

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Observation dfdb5fa9-6ba7-41c4-815f-a2ef542d3d10 · outbound

This paper cites Implicit gradient alignment in distributed and federated learning,.

Accelerated Training of Federated Learning via Second-Order Methods Implicit gradient alignment in distributed and federated learning,

Reference 6

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Observation 69a7c94a-a817-4632-b7db-c51eb7d48bf7 · outbound

This paper cites Handling data heterogeneity in federated learning with global data distribution.

Accelerated Training of Federated Learning via Second-Order Methods Handling data heterogeneity in federated learning with global data distribution

Reference 7

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Observation 6b8927cb-90f4-4b83-a582-3777385fe97c · outbound

This paper cites With a little help from my friend: Server-aided federated learning with partial client participation,.

Accelerated Training of Federated Learning via Second-Order Methods With a little help from my friend: Server-aided federated learning with partial client participation,

Reference 8

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Observation ed92cad2-92de-4f6e-872e-6fb942393d0b · outbound

This paper cites Achieving linear speedup with partial worker participation in non-iid federated learning,.

Accelerated Training of Federated Learning via Second-Order Methods Achieving linear speedup with partial worker participation in non-iid federated learning,

Reference 9

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Observation b736af08-a385-4deb-b515-cabe3e975273 · outbound

This paper cites Fast federated learning in the presence of arbitrary device unavailability,.

Accelerated Training of Federated Learning via Second-Order Methods Fast federated learning in the presence of arbitrary device unavailability,

Reference 10

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Observation 93b9537c-66e3-415f-9a9e-fc4f0af449bc · outbound

This paper cites Anchor sampling for federated learning with partial client participation,.

Accelerated Training of Federated Learning via Second-Order Methods Anchor sampling for federated learning with partial client participation,

Reference 11

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Observation 4f054c2f-c954-4217-b616-72c75ab68794 · outbound

This paper cites Fedvarp: Tackling the variance due to partial client participation in federated learning,.

Accelerated Training of Federated Learning via Second-Order Methods Fedvarp: Tackling the variance due to partial client participation in federated learning,

Reference 12

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Observation 6ecbdfa4-b7c2-4fee-a572-3e0bf742cc51 · outbound

This paper cites Federated learning with differential privacy: Algorithms and performance analysis,.

Accelerated Training of Federated Learning via Second-Order Methods Federated learning with differential privacy: Algorithms and performance analysis,

Reference 13

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Observation e3a7a57e-adc9-46ed-8d1c-1543f53ad56d · outbound

This paper cites Ldp-fed: Federated learning with local differential privacy,.

Accelerated Training of Federated Learning via Second-Order Methods Ldp-fed: Federated learning with local differential privacy,

Reference 14

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Observation 3b5cd932-897a-4a6c-9695-4f1510a05874 · outbound

This paper cites Federated learning and differential privacy for medical image analysis,.

Accelerated Training of Federated Learning via Second-Order Methods Federated learning and differential privacy for medical image analysis,

Reference 15

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Observation 67b4a4c0-f21e-451f-a57c-dd742ecea5f8 · outbound

This paper cites Federated learning with bayesian differ- ential privacy,.

Accelerated Training of Federated Learning via Second-Order Methods Federated learning with bayesian differ- ential privacy,

Reference 16

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Observation dcb83a83-bf50-487a-88e6-2b8440bbc484 · outbound

This paper cites Differential privacy meets federated learning under communication constraints,.

Accelerated Training of Federated Learning via Second-Order Methods Differential privacy meets federated learning under communication constraints,

Reference 17

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Observation 6ea51a52-9ef5-4cbe-b224-13cffdf60501 · outbound

This paper cites Attack of the tails: Yes, you really can backdoor federated learning,.

Accelerated Training of Federated Learning via Second-Order Methods Attack of the tails: Yes, you really can backdoor federated learning,

Reference 18

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Observation 24276563-05f6-4760-8e1f-b4c21f9bb295 · outbound

This paper cites Exploring adversarial attacks in federated learning for medical imaging,.

Accelerated Training of Federated Learning via Second-Order Methods Exploring adversarial attacks in federated learning for medical imaging,

Reference 19

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Observation 8012f483-5394-4359-bdf3-90601c4e9738 · outbound

This paper cites Analyzing user-level privacy attack against federated learning,.

Accelerated Training of Federated Learning via Second-Order Methods Analyzing user-level privacy attack against federated learning,

Reference 20

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Observation d656876c-380e-4a75-9b17-1f8a231dcbf6 · outbound

This paper cites Toward federated learning models resistant to adversarial attacks,.

Accelerated Training of Federated Learning via Second-Order Methods Toward federated learning models resistant to adversarial attacks,

Reference 21

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Observation a3d9ccb9-bb0e-4654-8160-f3bfa11ab05b · outbound

This paper cites Zero knowledge clustering based adversarial mitigation in heterogeneous federated learning,.

Accelerated Training of Federated Learning via Second-Order Methods Zero knowledge clustering based adversarial mitigation in heterogeneous federated learning,

Reference 22

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Observation 73b4e403-80a3-43f0-94d4-85c4e99e0a59 · outbound

This paper cites Giant: Globally improved approximate newton method for distributed optimization,.

Accelerated Training of Federated Learning via Second-Order Methods Giant: Globally improved approximate newton method for distributed optimization,

Reference 23

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Observation d949a60b-85be-4d9a-825e-2fc7d307bdbd · outbound

This paper cites LocalNewton: Reducing Communication Bottleneck for Distributed Learning.

Accelerated Training of Federated Learning via Second-Order Methods LocalNewton: Reducing Communication Bottleneck for Distributed Learning

Reference 24

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Observation c666d768-aed3-4e7b-aeba-3f756c0e3836 · outbound

This paper cites FedSSO: A Federated Server-Side Second-Order Optimization Algorithm.

Accelerated Training of Federated Learning via Second-Order Methods FedSSO: A Federated Server-Side Second-Order Optimization Algorithm

Reference 25

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Observation 9c630a9a-1f63-4c3d-8bec-756006c38ea3 · outbound

This paper cites Communication-efficient dis- tributed optimization using an approximate newton-type method,.

Accelerated Training of Federated Learning via Second-Order Methods Communication-efficient dis- tributed optimization using an approximate newton-type method,

Reference 26

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Observation 2028b3aa-9d35-411b-8d4e-aa88626244d2 · outbound

This paper cites Fednl: Making newton-type methods applicable to federated learning,.

Accelerated Training of Federated Learning via Second-Order Methods Fednl: Making newton-type methods applicable to federated learning,

Reference 27

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Observation 1c5c307e-60fe-4a97-870a-357778292e00 · outbound

This paper cites Nys-fl: A communication efficient federated learning with nystr ¨om approximated global newton direc- tion,.

Accelerated Training of Federated Learning via Second-Order Methods Nys-fl: A communication efficient federated learning with nystr ¨om approximated global newton direc- tion,

Reference 28

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Observation 8fa17e95-0245-4741-871c-b0cea026cc0d · outbound

This paper cites Fonn: Federated optimization with nys-newton,.

Accelerated Training of Federated Learning via Second-Order Methods Fonn: Federated optimization with nys-newton,

Reference 29

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Observation b97e7c09-9f01-4a53-8a5d-52f76cee3e31 · outbound

This paper cites Over-the-air federated learning via second-order optimization,.

Accelerated Training of Federated Learning via Second-Order Methods Over-the-air federated learning via second-order optimization,

Reference 30

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Observation e283f66d-0c59-434d-8b8b-20c5e1ae087b · outbound

This paper cites Foplahd: Federated optimization using locally approximated hessian diagonal,.

Accelerated Training of Federated Learning via Second-Order Methods Foplahd: Federated optimization using locally approximated hessian diagonal,

Reference 31

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Observation d1984c70-7798-407b-b588-3f080e0622c6 · outbound

This paper cites Done: distributed approximate newton-type method for federated edge learning,.

Accelerated Training of Federated Learning via Second-Order Methods Done: distributed approximate newton-type method for federated edge learning,

Reference 32

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Observation 4a769606-e0a8-47eb-a0cc-773e5825fb85 · outbound

This paper cites Freng: Federated optimization by using regularized natural gradient descent,.

Accelerated Training of Federated Learning via Second-Order Methods Freng: Federated optimization by using regularized natural gradient descent,

Reference 33

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Observation fd259a70-5743-484e-abc0-106679c6f6de · outbound

This paper cites Federated learning review: Fundamentals, enabling technologies, and future applications,.

Accelerated Training of Federated Learning via Second-Order Methods Federated learning review: Fundamentals, enabling technologies, and future applications,

Reference 34

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Observation 2f64f7e0-20da-4e65-866e-d3727efa2b9f · outbound

This paper cites The impact of adversarial attacks on federated learning: A survey,.

Accelerated Training of Federated Learning via Second-Order Methods The impact of adversarial attacks on federated learning: A survey,

Reference 35

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Observation d4709ccb-69ee-401a-b4a9-179c2ae54448 · outbound

This paper cites A systematic survey for differential privacy techniques in federated learning,.

Accelerated Training of Federated Learning via Second-Order Methods A systematic survey for differential privacy techniques in federated learning,

Reference 36

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raw_fallback, observed 2026-08-07T12:45:45.379516Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation e1590fef-e828-4da9-94b2-af3b2994af8a · outbound

This paper cites Differential privacy federated learning: A comprehensive review.

Accelerated Training of Federated Learning via Second-Order Methods Differential privacy federated learning: A comprehensive review

Reference 37

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raw_fallback, observed 2026-08-07T12:45:45.113888Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation a2adc8cc-d703-485a-b008-ecf0817d0479 · outbound

This paper cites Differentially private federated learning: A systematic review,.

Accelerated Training of Federated Learning via Second-Order Methods Differentially private federated learning: A systematic review,

Reference 38

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:45:30.544139Z digest=sha256:ffbdc6215a020724570ed9bc4d9cac85ea630384cd4d81a41a508c1460b69296

Observation e94125e3-ab15-4e53-8a2b-47b84b91c681 · outbound

This paper cites A survey of security threats in federated learning,.

Accelerated Training of Federated Learning via Second-Order Methods A survey of security threats in federated learning,

Reference 39

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verified fuzzy
raw_fallback, observed 2026-08-07T12:45:44.920369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T12:45:30.610354Z digest=sha256:2fd8c2d67493bce8a9b674ed1a5d7e3866e7f1182939e69fca3b49972a03c5f0

Observation f2b31969-e466-4b38-b7ef-43dbdae879d6 · outbound

This paper cites Challenges, applications and design aspects of federated learning: A survey.

Accelerated Training of Federated Learning via Second-Order Methods Challenges, applications and design aspects of federated learning: A survey

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:45:44.678999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T12:45:30.727848Z digest=sha256:e194af7e972f52bf02c8ca8d08e320f0cbc2ce4c607e7f53756a115b05e0d9a1

Observation 0af9acf5-60c0-4d2a-907c-f7ebad77893c · outbound

This paper cites Federated learning on non-iid data: A survey,.

Accelerated Training of Federated Learning via Second-Order Methods Federated learning on non-iid data: A survey,

Reference 41

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no resolver link, observed 2026-08-07T12:45:30.826582Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:45:30.826582Z digest=sha256:8aba09e078bee6801f70b33ce708b89405229f65d525c68998a32eb39603f2ef

Observation f4d71504-943f-4add-bf07-00213b667d67 · outbound

This paper cites Federated learning with non-iid data: A survey,.

Accelerated Training of Federated Learning via Second-Order Methods Federated learning with non-iid data: A survey,

Reference 42

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no resolver link, observed 2026-08-07T12:45:30.900776Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:45:30.900776Z digest=sha256:9bdebbc1508d306b394d7bdf87ea12169884af6d36e4590b549e9f282a0662de

Observation 37d7311a-cb42-4943-b1b1-11bce29f7f36 · outbound

This paper cites A survey of federated learning on non-iid data,.

Accelerated Training of Federated Learning via Second-Order Methods A survey of federated learning on non-iid data,

Reference 43

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verified fuzzy
raw_fallback, observed 2026-08-07T12:45:44.438290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T12:45:30.983094Z digest=sha256:0ee72fd4c828998c5e237b443db6b94bc83a85ed7de01c8534e8b9cfaecd29f8

Observation 4485da2b-fa45-426c-aff9-4113a80c4045 · outbound

This paper cites Federated learning for generalization, robustness, fairness: A survey and benchmark,.

Accelerated Training of Federated Learning via Second-Order Methods Federated learning for generalization, robustness, fairness: A survey and benchmark,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:45:44.170303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T12:45:31.127533Z digest=sha256:0e76ffcae85ee4622092ae30d5a8d2824902621d501ad43fe94b34e74e874678

Observation f390a9f7-a62a-42eb-90bb-6bd65a25c935 · outbound

This paper cites Federated Learning with Non-IID Data.

Accelerated Training of Federated Learning via Second-Order Methods Federated Learning with Non-IID Data

Reference 45

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no resolver link, observed 2026-08-07T12:45:31.209096Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:45:31.209096Z digest=sha256:950135bd7a9cc856e631ddeb0fa360cab03d10238c87a7e08016f243c0090b95

Observation 1cd69a4c-9d9f-4ab7-a2a9-5ee97420f57b · outbound

This paper cites On Second-order Optimization Methods for Federated Learning.

Accelerated Training of Federated Learning via Second-Order Methods On Second-order Optimization Methods for Federated Learning

Reference 46

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unresolved
no resolver link, observed 2026-08-07T12:45:31.278385Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:45:31.278385Z digest=sha256:e2385330c9d7b2e9501e84fabfe93a0bbaa85cc5c3dc3d4da550d6c77e56e016

Observation a3c77e43-a95e-4227-8673-48cdcb2086cf · outbound

This paper cites Review of second-order optimization techniques in artificial neural networks backpropagation,.

Accelerated Training of Federated Learning via Second-Order Methods Review of second-order optimization techniques in artificial neural networks backpropagation,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:45:43.961640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T12:45:31.361843Z digest=sha256:7f217f56be9e1aa2d648c5544898dd1d7143747d9309a2105065aef16d98abf9

Observation 3ea2d6ac-073c-4a98-a338-fb4af51b388d · outbound

This paper cites A survey of deep learning optimizers -- first and second order methods.

Accelerated Training of Federated Learning via Second-Order Methods A survey of deep learning optimizers -- first and second order methods

Reference 48

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no resolver link, observed 2026-08-07T12:45:31.457655Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:45:31.457655Z digest=sha256:5e7457644e6e25886ca6048e2129352a1a69ecf311e5d294b9a2e3a35d4bd422

Observation d2e9496a-096e-459b-a9f0-8dec0165a91a · outbound

This paper cites A state-of-the-art survey on solving non-iid data in federated learning,.

Accelerated Training of Federated Learning via Second-Order Methods A state-of-the-art survey on solving non-iid data in federated learning,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:45:43.682224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T12:45:31.545468Z digest=sha256:e255284ab99329a87298e87653afa393694548f8ebacf61064fd56b2526f0c05

Observation 12ca4a03-1487-483f-b729-29983af033ab · outbound

This paper cites Stochastic gradient descent,.

Accelerated Training of Federated Learning via Second-Order Methods Stochastic gradient descent,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:45:43.428451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T12:45:31.620157Z digest=sha256:acd7e9191f9666ff599ac63a5f1b5d1d3b612e8a2f54ce7843e18b8bf05ade18

Observation 7a627409-e68a-4db0-825b-ab0e5381f186 · outbound

This paper cites Nys-Newton: Nystr\"om-Approximated Curvature for Stochastic Optimization.

Accelerated Training of Federated Learning via Second-Order Methods Nys-Newton: Nystr\"om-Approximated Curvature for Stochastic Optimization

Reference 51

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no resolver link, observed 2026-08-07T12:45:31.716191Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:45:31.716191Z digest=sha256:6317ccc9d4c7a083e2a856b358170ada0090c2dad378388d03d337d2e6590ff5

Observation 734069cc-652b-49d4-8c61-864ed35a7880 · outbound

This paper cites Second-order stochastic optimization for machine learning in linear time,.

Accelerated Training of Federated Learning via Second-Order Methods Second-order stochastic optimization for machine learning in linear time,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:45:43.197752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T12:45:31.791426Z digest=sha256:8c58a5e98ff581491bad96c256695cf2268f2ef18c9e928589f21f3191ccf16f

Observation 2371cf0d-9d81-4e81-a4c6-85836820e127 · outbound

This paper cites Distributed estimation of the inverse hessian by determinantal averaging,.

Accelerated Training of Federated Learning via Second-Order Methods Distributed estimation of the inverse hessian by determinantal averaging,

Reference 53

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no resolver link, observed 2026-08-07T12:45:31.895514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:45:31.895514Z digest=sha256:7b4a62619c8f75c8d95985fc4c89e96af7d9b7e9c335335c89ab3028b637b55c

Observation 4cae4526-c918-4e24-bb50-6b15feb0bf67 · outbound

This paper cites Deep learning via hessian-free optimization.

Accelerated Training of Federated Learning via Second-Order Methods Deep learning via hessian-free optimization

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:45:42.973091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T12:45:31.984600Z digest=sha256:cea9b2a3f8c751cea590f27efb6f163a612ba31789bb61cce86915946a118214

Observation aa9fd46d-6c13-46ac-a938-e8289561c5c6 · outbound

This paper cites Hessian-free optimization for learning deep multidimensional recurrent neural networks,.

Accelerated Training of Federated Learning via Second-Order Methods Hessian-free optimization for learning deep multidimensional recurrent neural networks,

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:45:42.699217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T12:45:32.149953Z digest=sha256:90d5600904a89f7c672e4a7be182e1be1403830bb45355c761af442fa1b7cc77

Observation 825bbb58-c483-4b3b-be27-04103fdb5e88 · outbound

This paper cites Communication-efficient dis- tributed optimization using an approximate newton-type method,.

Accelerated Training of Federated Learning via Second-Order Methods Communication-efficient dis- tributed optimization using an approximate newton-type method,

Reference 56

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no resolver link, observed 2026-08-07T12:45:32.250343Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:45:32.250343Z digest=sha256:5a0982b366e05756548a7b8e30bf9b8bc62a817163be166feaca09290948ee3a

Observation ef089ef0-00df-4854-9a3e-a092bd2d8f9c · outbound

This paper cites Disco: Distributed optimization for self- concordant empirical loss,.

Accelerated Training of Federated Learning via Second-Order Methods Disco: Distributed optimization for self- concordant empirical loss,

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:45:42.429305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T12:45:32.329800Z digest=sha256:a0465416ec92747a6446bc96f56419bfad118b89bbefd567c622286d33b0a37b

Observation 7abcc974-bf83-4b32-8e63-fdae170055b2 · outbound

This paper cites AIDE: Fast and Communication Efficient Distributed Optimization.

Accelerated Training of Federated Learning via Second-Order Methods AIDE: Fast and Communication Efficient Distributed Optimization

Reference 58

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no resolver link, observed 2026-08-07T12:45:32.433055Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:45:32.433055Z digest=sha256:6ca548f8daab9888dc46e2bb7b021f61d0f5ceca6d335e84651f2858be176651

Observation 9f35c250-ba4b-4a6b-9050-5bb131f8ac38 · outbound

This paper cites Stochastic dual coordinate ascent methods for regularized loss,.

Accelerated Training of Federated Learning via Second-Order Methods Stochastic dual coordinate ascent methods for regularized loss,

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:45:41.965343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T12:45:32.650499Z digest=sha256:26bcad82fa1265e1838e3152d9744e1c9409d932a68d6c7c4e9656eb2b4d62f8

Observation 735e093d-538c-4987-9b40-93235dcbae0c · outbound

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

Accelerated Training of Federated Learning via Second-Order Methods Gradient-based learning applied to document recognition,

Reference 61

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no resolver link, observed 2026-08-07T12:45:32.762039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:45:32.762039Z digest=sha256:d8b5f5fd8183b93a39999a75c1d340090f020cc06a9c7317a67e16cbcf891f7a

Observation fa3e3d38-7747-4658-962a-0536b8a3502d · outbound

This paper cites Parallelized stochastic gradient descent,.

Accelerated Training of Federated Learning via Second-Order Methods Parallelized stochastic gradient descent,

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:45:41.721796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T12:45:32.826722Z digest=sha256:2a6f1183caf7d2dda455dc4c09fff2cd7993dced979abdba932840032131e113

Observation 51b87bb1-5678-48b7-ad99-e87aa655dcb7 · outbound

This paper cites Distributed optimization and statistical learning via the alternating direction method of multipliers,.

Accelerated Training of Federated Learning via Second-Order Methods Distributed optimization and statistical learning via the alternating direction method of multipliers,

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-07T12:45:32.876244Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:45:32.876244Z digest=sha256:f70f033da97992c4f8494b99bf852f8db3dc296a39e2d47cc1e1ae1151b8a9b5

Observation 27ef09fc-5b00-4fa2-96a1-f8c7abb7ff78 · outbound

This paper cites Quartz: Randomized dual coordi- nate ascent with arbitrary sampling,.

Accelerated Training of Federated Learning via Second-Order Methods Quartz: Randomized dual coordi- nate ascent with arbitrary sampling,

Reference 64

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verified fuzzy
raw_fallback, observed 2026-08-07T12:45:41.509016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T12:45:32.959039Z digest=sha256:bab1547427aa9af9329b91b0c814e446c03380b386b7703898be827785405736

Observation 129a8fe0-4d54-46af-af43-e3e302f1faff · outbound

This paper cites A universal catalyst for first-order optimization,.

Accelerated Training of Federated Learning via Second-Order Methods A universal catalyst for first-order optimization,

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:45:41.248420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T12:45:33.000486Z digest=sha256:c5ee389c0ac9f2458d5a6578387e0e6498735f30df7eb221287813bf707cb0c9

Observation 469006d8-52e8-45b1-815d-59c48d0396a4 · outbound

This paper cites Libsvm: a library for support vector machines,.

Accelerated Training of Federated Learning via Second-Order Methods Libsvm: a library for support vector machines,

Reference 66

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no resolver link, observed 2026-08-07T12:45:33.055909Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:45:33.055909Z digest=sha256:66e4675c33708bd8c9cfabd913edea1b35211503ca8a2d1e0ac51b753975b33f

Observation bb82be58-c482-4694-9d1d-ab4852684c8c · outbound

This paper cites Distributed optimization with arbitrary local solvers: Co- coa+ and beyond,.

Accelerated Training of Federated Learning via Second-Order Methods Distributed optimization with arbitrary local solvers: Co- coa+ and beyond,

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:45:41.013864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T12:45:33.114279Z digest=sha256:56fe0d46f26e1d73106ae6463690fa04f9a15cb877f715eae9baf0bdad08ba29

Observation 1ef97720-65ed-4097-b68a-4acfc473b56f · outbound

This paper cites LEAF: A Benchmark for Federated Settings.

Accelerated Training of Federated Learning via Second-Order Methods LEAF: A Benchmark for Federated Settings

Reference 68

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no resolver link, observed 2026-08-07T12:45:33.167489Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:45:33.167489Z digest=sha256:3304cbe45825131740d9fbd9fddf471fd45fbc86433dffbe6b2d136d7695dca0

Observation 8d18858a-0e3b-4fe2-9faa-772481bc15d5 · outbound

This paper cites Federated optimization in heterogeneous networks,.

Accelerated Training of Federated Learning via Second-Order Methods Federated optimization in heterogeneous networks,

Reference 69

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no resolver link, observed 2026-08-07T12:45:33.203083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:45:33.203083Z digest=sha256:27486432ab09a848493823b2111cf7878e13da8e55f83f7828c5c94b2f69d8b7

Observation 69ebaad9-1f65-4960-966d-caca1eb1f777 · outbound

This paper cites an unresolved cited work.

Accelerated Training of Federated Learning via Second-Order Methods Unresolved cited work

Reference 70

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no resolver link, observed 2026-08-07T12:45:33.301663Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:45:33.301663Z digest=sha256:780c9cbc1bbb4e995f9845ea98cb711de284d20a44b8cc86ab910d3f6a8d27e2

Observation c51b3be7-f461-4dae-8059-dc6af0b73b1b · outbound

This paper cites Nesterov, Introductory lectures on convex optimization: A basic course.

Accelerated Training of Federated Learning via Second-Order Methods Nesterov, Introductory lectures on convex optimization: A basic course

Reference 71

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no resolver link, observed 2026-08-07T12:45:33.369256Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:45:33.369256Z digest=sha256:5a3efd75db767153b5d54237d89b3f633b855c8e06ca4588e6c224e416d35ff7

Observation b29a5435-78b2-4597-bf01-6e9ef20a295d · outbound

This paper cites On the limited memory bfgs method for large scale optimization,.

Accelerated Training of Federated Learning via Second-Order Methods On the limited memory bfgs method for large scale optimization,

Reference 72

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no resolver link, observed 2026-08-07T12:45:33.439585Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:45:33.439585Z digest=sha256:f8f166a4ac5829680e091c0600515b84c6c87cc68c7ccca7e20d0c9a3ef71874

Observation 417aede5-1a2e-48e4-a71a-43e3a7d1070d · outbound

This paper cites Conjugate gradient method,.

Accelerated Training of Federated Learning via Second-Order Methods Conjugate gradient method,

Reference 73

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no resolver link, observed 2026-08-07T12:45:33.517810Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:45:33.517810Z digest=sha256:7c14f4dd3f9541eafe61f5e81632c436c39528a4a2885cb38ae00d6ec6d7f71e

Observation 262efced-12e0-49fe-a01b-343f63f26c3f · outbound

This paper cites Classical iterative methods for linear systems,.

Accelerated Training of Federated Learning via Second-Order Methods Classical iterative methods for linear systems,

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:45:40.771266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T12:45:33.551343Z digest=sha256:94f83dced9c234baf45e6544a0598b5eddb981dfa51285cd98fe8e0f3e2d9491

Observation 36a06d16-c706-4fa8-8915-7a84552b90df · outbound

This paper cites Emnist: Extending mnist to handwritten letters,.

Accelerated Training of Federated Learning via Second-Order Methods Emnist: Extending mnist to handwritten letters,

Reference 75

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unresolved
no resolver link, observed 2026-08-07T12:45:33.610836Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:45:33.610836Z digest=sha256:411e2f22d7b3f19385634d4e0cfdf3c6a0269f0300b8a8535550619ae6eb31b4

Observation b794997c-d412-4ad7-9c9c-f4571591beda · outbound

This paper cites A public domain dataset for human activity recognition using smart- phones.

Accelerated Training of Federated Learning via Second-Order Methods A public domain dataset for human activity recognition using smart- phones

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:45:40.543834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T12:45:33.674742Z digest=sha256:9f5207f09f87a6e14fd2c705186fde5a1f1fadc3684da2ecfe44a31237d58e73

Observation 84a12788-1362-4ae5-938a-bf3ee4eb84e8 · outbound

This paper cites Basis matters: Better communication-efficient second order methods for federated learning,.

Accelerated Training of Federated Learning via Second-Order Methods Basis matters: Better communication-efficient second order methods for federated learning,

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:45:40.299164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T12:45:33.712300Z digest=sha256:e1013f50e3a49f8a50867a45ae8dda894c4130db47a217d6a1771743ccdc1099

Observation 1c9ac396-c4d2-4a34-bd69-cae1c2c74083 · outbound

This paper cites Fednew: A communication-efficient and privacy-preserving newton-type method for federated learning,.

Accelerated Training of Federated Learning via Second-Order Methods Fednew: A communication-efficient and privacy-preserving newton-type method for federated learning,

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:45:40.091920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T12:45:33.773512Z digest=sha256:e70b818adc3d860dfc3cea05acf1118f2b8279592b65ef9a8404af73681b90ba

Observation 0c00a818-de6a-4cc7-bcec-dfaf70c6178e · outbound

This paper cites Shed: A newton- type algorithm for federated learning based on incremental hessian eigenvector sharing,.

Accelerated Training of Federated Learning via Second-Order Methods Shed: A newton- type algorithm for federated learning based on incremental hessian eigenvector sharing,

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:45:39.839316Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T12:45:33.846972Z digest=sha256:6e9a917332b4e689e8be0faa59740334a0787dec3339d013026380de6a12bf46

Observation 41f71537-ffc3-4575-9e10-03efdfebccab · outbound

This paper cites Fedns: A fast sketching newton- type algorithm for federated learning,.

Accelerated Training of Federated Learning via Second-Order Methods Fedns: A fast sketching newton- type algorithm for federated learning,

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:45:39.657153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T12:45:33.921804Z digest=sha256:3db9ce6d0a0d1fdf2c1c49e6227476e7f6e98268063fd38dbaaf8e19f509f6cd

Observation 43e01e03-a6bc-4886-b34d-5d6f0740fb0e · outbound

This paper cites Distributed second order meth- ods with fast rates and compressed communication,.

Accelerated Training of Federated Learning via Second-Order Methods Distributed second order meth- ods with fast rates and compressed communication,

Reference 81

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:45:39.512491Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T12:45:33.990127Z digest=sha256:96cd82883b0083214c3860dc898d8c0c2d6c5975fed71cc4c22476ee7f25b063

Observation b89b3554-9151-4b02-a2de-fe46311b352e · outbound

This paper cites Distributed learning with compressed gradient differences,.

Accelerated Training of Federated Learning via Second-Order Methods Distributed learning with compressed gradient differences,

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:45:39.370888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T12:45:34.032026Z digest=sha256:ca36235b4d672ab1fede565b2a59b1691e9707b6aabbcf01c2918501cb1a34ae

Observation 89058f18-f7fb-4377-beb1-e3b909821eaa · outbound

This paper cites Acceleration for Compressed Gradient Descent in Distributed and Federated Optimization.

Accelerated Training of Federated Learning via Second-Order Methods Acceleration for Compressed Gradient Descent in Distributed and Federated Optimization

Reference 83

Resolution
unresolved
no resolver link, observed 2026-08-07T12:45:34.096395Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:45:34.096395Z digest=sha256:a809674c4845a2a981dba84f0c73d8bb2ee137e5cbbebb3f223be4878b94e97a

Observation 4cf7675d-c7e0-43a9-9af2-346e20ec8e5e · outbound

This paper cites Local sgd: Unified theory and new efficient methods,.

Accelerated Training of Federated Learning via Second-Order Methods Local sgd: Unified theory and new efficient methods,

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:45:39.175730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T12:45:34.167230Z digest=sha256:ffe4da46fc5ca0143bc437b3ded4d1a12064ac3a4f29697f06899a04d4b37de5

Observation 70c52783-d691-40f6-96c0-5409e7d639d6 · outbound

This paper cites Dingo: Distributed newton-type method for gradient-norm optimization,.

Accelerated Training of Federated Learning via Second-Order Methods Dingo: Distributed newton-type method for gradient-norm optimization,

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:45:38.997858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T12:45:34.195292Z digest=sha256:dd099911cfaf0ad182cdefb436d07f184901cadcd410e32de0df59ec3e006ed8

Observation 1b436ac3-24e3-480b-b0ee-190a6f531777 · outbound

This paper cites Stephen j,.

Accelerated Training of Federated Learning via Second-Order Methods Stephen j,

Reference 86

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:45:38.834809Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T12:45:34.255524Z digest=sha256:9868a127e2b9132d63f206f78fc6dae334f4f888560ba7802f1547b469e86c42

Observation f853cdc8-1234-4659-9073-1121517d2cab · outbound

This paper cites Distributed Quasi-Newton Method for Fair and Fast Federated Learning.

Accelerated Training of Federated Learning via Second-Order Methods Distributed Quasi-Newton Method for Fair and Fast Federated Learning

Reference 87

Resolution
verified exact
local_arxiv, observed 2026-08-07T12:45:36.133511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T12:45:34.307124Z digest=sha256:9048279ec763269a5047eed9f474ae3437f3d5e2ba16454397e4ca666ddfddec

Observation 3f2c0269-b24a-4772-a164-dc418fc9c702 · outbound

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

Accelerated Training of Federated Learning via Second-Order Methods Learning multiple layers of features from tiny images,

Reference 88

Resolution
unresolved
no resolver link, observed 2026-08-07T12:45:34.354154Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:45:34.354154Z digest=sha256:628ab633f86f60d0fdece5ded9119730f65519a4c60ffdd7fa2b0ea558f7788e

Observation 2e9d8ae5-9d2f-4329-9210-9e1bde5e309c · outbound

This paper cites Federated accelerated stochastic gradient descent,.

Accelerated Training of Federated Learning via Second-Order Methods Federated accelerated stochastic gradient descent,

Reference 89

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:45:38.461724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T12:45:34.444648Z digest=sha256:cef9b22f68afcdecf881a3bc7bc78fca2f9af8203928044eefacab3a5185bd71

Observation 837ad19f-3b89-4d20-bbd9-6e8fa8bd9669 · outbound

This paper cites Adaptive Federated Optimization.

Accelerated Training of Federated Learning via Second-Order Methods Adaptive Federated Optimization

Reference 90

Resolution
unresolved
no resolver link, observed 2026-08-07T12:45:34.551914Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:45:34.551914Z digest=sha256:f750e6968f2923ead93208af52bfddde428b4977314e4f24a0e2e37ea04ac636

Observation 637e7a52-e486-4ebc-b75d-df62b2de42ab · outbound

This paper cites Feddane: A federated newton-type method,.

Accelerated Training of Federated Learning via Second-Order Methods Feddane: A federated newton-type method,

Reference 91

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:45:42.178754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T12:45:34.605321Z digest=sha256:4aabc6e670bc84920947fcde14ff68d1cf5dfe42af4818678cf45a62fee92006

Observation aa8c6a64-54d2-4fc8-9661-059ea1fb13a3 · outbound

This paper cites Algorithms for multicriterion optimization,.

Accelerated Training of Federated Learning via Second-Order Methods Algorithms for multicriterion optimization,

Reference 92

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:45:38.301472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T12:45:34.683605Z digest=sha256:df45be6c7b24bad0ce8f00cad21c6910ddb13e392d735844c9b0c7cd762baae0

Observation e5336fbd-84b5-4db8-9c3e-50d0aa64f3de · outbound

This paper cites Tiny imagenet visual recognition challenge,.

Accelerated Training of Federated Learning via Second-Order Methods Tiny imagenet visual recognition challenge,

Reference 93

Resolution
unresolved
no resolver link, observed 2026-08-07T12:45:34.739280Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:45:34.739280Z digest=sha256:592e0086b1578ff5fbd59e87c9d1fa31814124c1dedfd2ab9dc93bd2846e62ef

Observation 042027fe-c359-492d-99cd-154f2eeba8b0 · outbound

This paper cites CINIC-10 is not ImageNet or CIFAR-10.

Accelerated Training of Federated Learning via Second-Order Methods CINIC-10 is not ImageNet or CIFAR-10

Reference 94

Resolution
unresolved
no resolver link, observed 2026-08-07T12:45:34.806195Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:45:34.806195Z digest=sha256:e8d7ab7db7d82405bfdf7f937a08bf52d8e790fb5bec4298ac97f25f5b3f29af

Observation 8e889ea8-c40a-4316-ad23-d16f1202447f · outbound

This paper cites Federated Learning with Fair Averaging.

Accelerated Training of Federated Learning via Second-Order Methods Federated Learning with Fair Averaging

Reference 95

Resolution
unresolved
no resolver link, observed 2026-08-07T12:45:34.890436Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:45:34.890436Z digest=sha256:4133bcb08491a5f68ffd5024ae96514827e495859f4328d87f0d269fb572fde8

Observation 3eedfa64-3e34-48d6-94b1-64156f2b7833 · outbound

This paper cites Federated Learning with Matched Averaging.

Accelerated Training of Federated Learning via Second-Order Methods Federated Learning with Matched Averaging

Reference 96

Resolution
unresolved
no resolver link, observed 2026-08-07T12:45:34.984741Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:45:34.984741Z digest=sha256:5236f61c56e05dadc23c49bbf98bb655a784e4a4b02e89688272610ecaab221f

Observation ffecdc73-a257-433a-ade0-b75792c8120a · outbound

This paper cites Deep residual learning for image recognition,.

Accelerated Training of Federated Learning via Second-Order Methods Deep residual learning for image recognition,

Reference 97

Resolution
unresolved
no resolver link, observed 2026-08-07T12:45:35.083460Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:45:35.083460Z digest=sha256:6186b850deab18d6fc45b0d10a6eb02db9d6090cee78342722a04d18cdb15407

Observation d9c58ee7-54f0-4b06-812c-27dfe75db371 · outbound

This paper cites Federated optimization with linear-time approximated hessian diagonal,.

Accelerated Training of Federated Learning via Second-Order Methods Federated optimization with linear-time approximated hessian diagonal,

Reference 98

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:45:38.171151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T12:45:35.178697Z digest=sha256:a3b4bcb42d5df05aac013f10c4ea89ab77ffbeca7255843d2577f44051f500f5

Observation 35a49397-52e5-43e9-8f42-8d0ef2e6e81e · outbound

This paper cites Robust federated learning under statistical heterogeneity via hessian-weighted aggregation,.

Accelerated Training of Federated Learning via Second-Order Methods Robust federated learning under statistical heterogeneity via hessian-weighted aggregation,

Reference 99

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:45:38.004326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T12:45:35.249638Z digest=sha256:366ceaba7500b0de87e09487df8c4426f5c80143890296a5b2e3da575d21ce0c

Observation c3bdacc9-a17a-406a-b1b5-cbcc14cb7195 · outbound

This paper cites Fed-sophia: A communication-efficient second-order federated learning algorithm,.

Accelerated Training of Federated Learning via Second-Order Methods Fed-sophia: A communication-efficient second-order federated learning algorithm,

Reference 100

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:45:37.813887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T12:45:35.351380Z digest=sha256:92114ab9583ce3bc522d3d4204fcbd09dc75e0b778ca7dba747b3aa22e7dc5b7

Observation f62ba3dd-bb8a-465b-95d3-b71fade0f26a · outbound

This paper cites An estimator for the diagonal of a matrix,.

Accelerated Training of Federated Learning via Second-Order Methods An estimator for the diagonal of a matrix,

Reference 101

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:45:37.601155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T12:45:35.436548Z digest=sha256:c8e8a07278406dc7755d8aee1616226167f699ae3f5a8c64ea3a1c5ae8d91bc3

Pith citing papers

No inbound Pith citation observations are available.