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Paper Citation Record · LEDGER

Sketched Gaussian Mechanism for Private Federated Learning

As of 22 August 2026, this Paper Citation Record lists 85 of 85 outbound references and 0 inbound Pith citation observations for arXiv:2509.08195.

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

pith.paper-citation-record.v1
2509.08195 v1

Coverage vector

measured 85 of 85 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T21:12:52.855661Z

measured 85 of 85 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

85 of 85 outbound references displayed

  • verified exact4
  • verified fuzzy52
  • unresolved29
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6cb1e314-afb0-4e06-bacc-a911159910ba · outbound

This paper cites Understanding clipping for federated learning: Convergence and client-level differential privacy.

Sketched Gaussian Mechanism for Private Federated Learning Understanding clipping for federated learning: Convergence and client-level differential privacy

Reference 1

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Observation 73d87887-0c7b-4472-a682-d33ae1938d53 · outbound

This paper cites Private and Communication-Efficient Federated Learning based on Differentially Private Sketches.

Sketched Gaussian Mechanism for Private Federated Learning Private and Communication-Efficient Federated Learning based on Differentially Private Sketches

Reference 2

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Observation 885a2945-dcb4-48eb-8a24-eff05f27c8ca · outbound

This paper cites Sketching for first order method: efficient al- gorithm for low-bandwidth channel and vulnerability.

Sketched Gaussian Mechanism for Private Federated Learning Sketching for first order method: efficient al- gorithm for low-bandwidth channel and vulnerability

Reference 3

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Observation 860bba57-edff-40e2-baf2-c3d871868209 · outbound

This paper cites Sketching for distributed deep learning: A sharper analysis.

Sketched Gaussian Mechanism for Private Federated Learning Sketching for distributed deep learning: A sharper analysis

Reference 4

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Observation 98fde843-1b17-4212-b507-ac7cac37dedd · outbound

This paper cites Brendan McMahan, Ilya Mironov, Kunal Talwar, and Li Zhang.

Sketched Gaussian Mechanism for Private Federated Learning Brendan McMahan, Ilya Mironov, Kunal Talwar, and Li Zhang

Reference 5

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Observation 4c5a28f9-2fef-42f7-bc59-5131d27c9d69 · outbound

This paper cites an unresolved cited work.

Sketched Gaussian Mechanism for Private Federated Learning Unresolved cited work

Reference 6

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Observation 1a7d5fed-3fdc-4a04-9347-c259b21c224f · outbound

This paper cites Wainwright, Peter L.

Sketched Gaussian Mechanism for Private Federated Learning Wainwright, Peter L

Reference 7

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Source-reported events for the cited work

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Observation 34a36743-c8d2-45b2-9676-8fc384aecb66 · outbound

This paper cites Finding frequent items in data streams.

Sketched Gaussian Mechanism for Private Federated Learning Finding frequent items in data streams

Reference 8

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Observation 677aea1a-df00-47a1-bff9-c496fbf33d2e · outbound

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

Sketched Gaussian Mechanism for Private Federated Learning Calibrating noise to sensitivity in private data analysis

Reference 9

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Observation f19e4b4a-e1d5-4eb8-831b-99b00cd7a8b7 · outbound

This paper cites Differentially Private Federated Learning: A Client Level Perspective.

Sketched Gaussian Mechanism for Private Federated Learning Differentially Private Federated Learning: A Client Level Perspective

Reference 10

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Observation 9acf48bf-5f6d-475d-b233-b8f689f0e041 · outbound

This paper cites D2P-Fed: Differentially Private Federated Learning With Efficient Communication.

Sketched Gaussian Mechanism for Private Federated Learning D2P-Fed: Differentially Private Federated Learning With Efficient Communication

Reference 11

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Observation a92e052d-9d26-4bee-9c49-5ba0d28d4ab6 · outbound

This paper cites Federated learning with Bayesian differential privacy.

Sketched Gaussian Mechanism for Private Federated Learning Federated learning with Bayesian differential privacy

Reference 12

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Observation d3d3e0c8-5563-4e8f-b0d2-6bc68f627dfa · outbound

This paper cites Stable Rank and Intrinsic Dimension of Real and Complex Matrices.

Sketched Gaussian Mechanism for Private Federated Learning Stable Rank and Intrinsic Dimension of Real and Complex Matrices

Reference 13

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Observation ebd7abd4-8207-4fcb-8f9e-0ea49e5240ef · outbound

This paper cites An investigation into neural net optimization via Hessian eigenvalue density.

Sketched Gaussian Mechanism for Private Federated Learning An investigation into neural net optimization via Hessian eigenvalue density

Reference 14

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Observation 54debbf4-ba4d-434c-a834-3ffc7fc686dd · outbound

This paper cites Hessian based analysis of SGD for deep nets: Dynamics and generalization.

Sketched Gaussian Mechanism for Private Federated Learning Hessian based analysis of SGD for deep nets: Dynamics and generalization

Reference 15

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Observation bd57ed43-8e23-4aee-b56d-253bba041ffb · outbound

This paper cites Sophia: A Scalable Stochastic Second-order Optimizer for Language Model Pre-training.

Sketched Gaussian Mechanism for Private Federated Learning Sophia: A Scalable Stochastic Second-order Optimizer for Language Model Pre-training

Reference 16

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Observation f646950f-0641-47e7-8df5-a85bfd2daaf3 · outbound

This paper cites Eigenvalues of the Hessian in Deep Learning: Singularity and Beyond.

Sketched Gaussian Mechanism for Private Federated Learning Eigenvalues of the Hessian in Deep Learning: Singularity and Beyond

Reference 17

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Observation 77f81e85-0a3b-4405-baf8-67ae205969f6 · outbound

This paper cites an unresolved cited work.

Sketched Gaussian Mechanism for Private Federated Learning Unresolved cited work

Reference 18

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Observation da3bf9bd-86e8-4011-9d01-6e968bd9c813 · outbound

This paper cites On the Power-Law Hessian Spectrums in Deep Learning.

Sketched Gaussian Mechanism for Private Federated Learning On the Power-Law Hessian Spectrums in Deep Learning

Reference 19

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Observation 97ac1617-c7de-4a19-8d93-597025ab19dd · outbound

This paper cites Why Transformers Need Adam: A Hessian Perspective.

Sketched Gaussian Mechanism for Private Federated Learning Why Transformers Need Adam: A Hessian Perspective

Reference 20

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Observation 32eac1fe-ebca-4b3e-81c2-9e477c1c7ec7 · outbound

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

Sketched Gaussian Mechanism for Private Federated Learning Communication-efficient learning of deep networks from decentralized data

Reference 21

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Observation bd38a1f0-30da-4202-b684-0465e3d5210e · outbound

This paper cites FedNL: Making Newton-Type Methods Applicable to Federated Learning.

Sketched Gaussian Mechanism for Private Federated Learning FedNL: Making Newton-Type Methods Applicable to Federated Learning

Reference 22

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Observation 2665af9f-ed34-477c-950f-4a8e52bf871b · outbound

This paper cites Momentum provably improves error feed- back!Advances in Neural Information Processing Systems, 36, 2024.

Sketched Gaussian Mechanism for Private Federated Learning Momentum provably improves error feed- back!Advances in Neural Information Processing Systems, 36, 2024

Reference 23

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Observation e1f410f8-a41a-4270-83e0-327535896515 · outbound

This paper cites FetchSGD: Communication-efficient federated learning with sketching.

Sketched Gaussian Mechanism for Private Federated Learning FetchSGD: Communication-efficient federated learning with sketching

Reference 24

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Observation 3db9492f-a44c-42f1-ba54-2295f4b8f930 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Sketched Gaussian Mechanism for Private Federated Learning Adam: A Method for Stochastic Optimization

Reference 25

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Observation 6676055f-7c97-4d41-9f09-12d5525ef01d · outbound

This paper cites Adaptive methods for nonconvex optimization.Advances in Neural Information Processing Systems, 31, 2018.

Sketched Gaussian Mechanism for Private Federated Learning Adaptive methods for nonconvex optimization.Advances in Neural Information Processing Systems, 31, 2018

Reference 26

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Observation a4cfab35-b12b-4a54-ab84-c5d8b8b2fcb9 · outbound

This paper cites Improved convergence of differential private SGD with gradient clipping.

Sketched Gaussian Mechanism for Private Federated Learning Improved convergence of differential private SGD with gradient clipping

Reference 27

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Observation 5c7f80f8-17eb-4d05-814e-7f202ca28686 · outbound

This paper cites Comprehensive privacy analysis of deep learning: Passive and active white-box inference attacks against centralized and federated learning.

Sketched Gaussian Mechanism for Private Federated Learning Comprehensive privacy analysis of deep learning: Passive and active white-box inference attacks against centralized and federated learning

Reference 28

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Observation 283b07f0-263c-4c73-b4b5-954e434f9e23 · outbound

This paper cites Information leaks in federated learning.

Sketched Gaussian Mechanism for Private Federated Learning Information leaks in federated learning

Reference 29

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Observation 0df0d5c4-579d-481c-bcb0-274a6b480545 · outbound

This paper cites DBA: Distributed backdoor attacks against federated learning.

Sketched Gaussian Mechanism for Private Federated Learning DBA: Distributed backdoor attacks against federated learning

Reference 30

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source=pdf_text observed=2026-08-04T21:12:52.127461Z digest=sha256:106a5854749457874a494d36ea132a29438a0d2094db30031e10fb366417f304

Observation 185ded53-f506-4cd6-b3f4-6b941656c205 · outbound

This paper cites iDLG: Improved Deep Leakage from Gradients.

Sketched Gaussian Mechanism for Private Federated Learning iDLG: Improved Deep Leakage from Gradients

Reference 31

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Observation a7d931bf-b3e6-4742-99ef-6803574e29bb · outbound

This paper cites Deep leakage from gradients.Advances in Neural Information Processing Systems, 32, 2019.

Sketched Gaussian Mechanism for Private Federated Learning Deep leakage from gradients.Advances in Neural Information Processing Systems, 32, 2019

Reference 32

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Observation 2ff8bba1-e1cb-4728-94ad-bedf54b7e018 · outbound

This paper cites Andersen, Jun Woo Park, Alexander J.

Sketched Gaussian Mechanism for Private Federated Learning Andersen, Jun Woo Park, Alexander J

Reference 33

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Observation b2b1e4a3-dcc2-452a-bc3d-00bd742b2132 · outbound

This paper cites Brendan McMahan, Brendan Avent, Aur ´elien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, et al.

Sketched Gaussian Mechanism for Private Federated Learning Brendan McMahan, Brendan Avent, Aur ´elien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, et al

Reference 34

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:12:52.422405Z digest=sha256:dd1418e7716cd793f7486d3f0b3bcf62da5eb71865c8b3bf001de560cb31272a

Observation 28420740-cf23-4032-adad-dc1d06964f06 · outbound

This paper cites Andersen, Alexander J.

Sketched Gaussian Mechanism for Private Federated Learning Andersen, Alexander J

Reference 35

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:12:52.526823Z digest=sha256:f295768abbe32882ef09195211d557805708b8d6073c500fa97375d4be718198

Observation 4fd12059-a8be-43c1-b2c4-3f461ff46945 · outbound

This paper cites Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training.

Sketched Gaussian Mechanism for Private Federated Learning Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training

Reference 36

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source=pdf_text observed=2026-08-04T21:12:52.601296Z digest=sha256:ecd5a49a2db423f7ba8a6a7f6fae6b361302c5b9bee40408d2a20870095664d3

Observation 097a903e-1ba1-45aa-9d01-9dfffa3e73da · outbound

This paper cites Atomo: Communication-efficient learning via atomic sparsification.Advances in Neural In- formation Processing Systems, 31, 2018.

Sketched Gaussian Mechanism for Private Federated Learning Atomo: Communication-efficient learning via atomic sparsification.Advances in Neural In- formation Processing Systems, 31, 2018

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:12:54.850468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:12:52.662245Z digest=sha256:1a5f31c469342aeef4e28cb4b944b6c224132fad63326b415e0c10048134ab4b

Observation 5abefdd8-72ce-4c46-b337-f0179d9d641c · outbound

This paper cites Inan, Berivan Isik, Ayfer Ozgur, and Tsachy Weissman.

Sketched Gaussian Mechanism for Private Federated Learning Inan, Berivan Isik, Ayfer Ozgur, and Tsachy Weissman

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:12:54.624542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:12:52.707590Z digest=sha256:0af381f6cbceb18372dafc72f8cd1f8f232db33a34f6d09dffc940c00a3db36e

Observation a48c6935-423a-42e0-beee-018463cfe1d4 · outbound

This paper cites QSGD: Communication- efficient SGD via gradient quantization and encoding.Advances in Neural Information Processing Sys- tems, 30, 2017.

Sketched Gaussian Mechanism for Private Federated Learning QSGD: Communication- efficient SGD via gradient quantization and encoding.Advances in Neural Information Processing Sys- tems, 30, 2017

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:12:54.345176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:12:52.710747Z digest=sha256:e36e99f9b89d4a0b8f1d676ded4b2a488811bd62f31a0b25da4b24121d192565

Observation 5f2710ca-8e7f-4afe-9380-dfd931fff0a9 · outbound

This paper cites Communication-efficient federated learning for heteroge- neous edge devices based on adaptive gradient quantization.

Sketched Gaussian Mechanism for Private Federated Learning Communication-efficient federated learning for heteroge- neous edge devices based on adaptive gradient quantization

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:12:54.107132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:12:52.713861Z digest=sha256:879f2d68b84d683df7db1cb21e6e93a120bf40a9552cb4d182d11e8d401303c6

Observation 2ea4794f-14a6-4073-92d4-4ea86d57b3d9 · outbound

This paper cites FedPAQ: A communication-efficient federated learning method with periodic averaging and quanti- zation.

Sketched Gaussian Mechanism for Private Federated Learning FedPAQ: A communication-efficient federated learning method with periodic averaging and quanti- zation

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:12:53.870976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:12:52.717193Z digest=sha256:c869e606ec3b0c16e345be8037eb94cfbfd9ab8b979dd2f9b1c228e7baf5d986

Observation c115bb44-dc6a-46a8-9768-d1056bccf986 · outbound

This paper cites Communication-efficient distributed SGD with sketching.Advances in Neural Information Processing Systems, 32, 2019.

Sketched Gaussian Mechanism for Private Federated Learning Communication-efficient distributed SGD with sketching.Advances in Neural Information Processing Systems, 32, 2019

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:12:53.719880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:12:52.720123Z digest=sha256:bfb3eac13395db39976223c4eafc47344a20861069f53bf4e7a7670bbeb515da

Observation eb9d3f31-8f91-4526-baaf-b2542484f5ac · outbound

This paper cites Stich, Jean-Baptiste Cordonnier, and Martin Jaggi.

Sketched Gaussian Mechanism for Private Federated Learning Stich, Jean-Baptiste Cordonnier, and Martin Jaggi

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:12:53.658522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:12:52.723419Z digest=sha256:51bc66520dbffce21d7c392f198c18e38e3e5a17430df2e2719a50406c20f358

Observation 5b19600b-3ff2-4bba-a22d-24ea19468357 · outbound

This paper cites LDP-Fed: Federated learning with local differential privacy.

Sketched Gaussian Mechanism for Private Federated Learning LDP-Fed: Federated learning with local differential privacy

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:12:53.610194Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:12:52.727289Z digest=sha256:4a911f64d02e2631c9b5ddb45231f4d69efc8bf4e57fe66888c72ef59b432649

Observation 2ddbaf9f-3b93-4be8-9b33-3b99030f8244 · outbound

This paper cites A hybrid approach to privacy-preserving federated learning.

Sketched Gaussian Mechanism for Private Federated Learning A hybrid approach to privacy-preserving federated learning

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:12:53.587634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:12:52.730266Z digest=sha256:448d7e4c0ede6022e55339b0458209d432bd83159716749ca2111d3035e33aef

Observation f3d4810c-bd71-4a1a-bcf7-081d81a44b79 · outbound

This paper cites Canonne, Gautam Kamath, and Thomas Steinke.

Sketched Gaussian Mechanism for Private Federated Learning Canonne, Gautam Kamath, and Thomas Steinke

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:12:53.567550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:12:52.733754Z digest=sha256:5e7424869f3b8260c63138fd1c72faeeeb4cdcc88fcaa1f404dcab85aec73bab

Observation b76e01a2-3435-44a9-abc0-4fc254701c87 · outbound

This paper cites Sparse Communication for Distributed Gradient Descent.

Sketched Gaussian Mechanism for Private Federated Learning Sparse Communication for Distributed Gradient Descent

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-04T21:12:52.736913Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T21:12:52.736913Z digest=sha256:89a34f5d5e5d0e6f7ffeeb51d8945d39e11d9259470b2bc711ad33870bb2a1e4

Observation 069ec941-891d-4576-9d44-d9aadcc68136 · outbound

This paper cites Yu, Sanjiv Kumar, and H.

Sketched Gaussian Mechanism for Private Federated Learning Yu, Sanjiv Kumar, and H

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:12:53.556211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:12:52.740367Z digest=sha256:5aba34af6990612fcb6ebfcfdbee1a008bb839515671a4c04a69a9a75e57c970

Observation dd15e354-d220-4c75-8193-f85f08027b99 · outbound

This paper cites TernGrad: Ternary gradients to reduce communication in distributed deep learning.Advances in Neural Informa- tion Processing Systems, 30, 2017.

Sketched Gaussian Mechanism for Private Federated Learning TernGrad: Ternary gradients to reduce communication in distributed deep learning.Advances in Neural Informa- tion Processing Systems, 30, 2017

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:12:53.544594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:12:52.743671Z digest=sha256:37a9e884f6b69e90d92abc77626b69be9cda42dace376a5e4d9ea1b5a341e584

Observation 075230c9-f2ab-4525-a6a8-924b243c4f81 · outbound

This paper cites Drive: One-bit distributed mean estimation.Advances in Neural Information Processing Sys- tems, 34:362–377, 2021.

Sketched Gaussian Mechanism for Private Federated Learning Drive: One-bit distributed mean estimation.Advances in Neural Information Processing Sys- tems, 34:362–377, 2021

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:12:53.532155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:12:52.746616Z digest=sha256:d5b49b882c73c58ddaa201ae8cfbbb888c957dd9fe464238e371390edc7679b9

Observation 874b6f07-da5f-4a85-b82e-e0538ee71772 · outbound

This paper cites Masked training of neural networks with partial gradients.

Sketched Gaussian Mechanism for Private Federated Learning Masked training of neural networks with partial gradients

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:12:53.517931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:12:52.749748Z digest=sha256:709aecf3e530fafd99d7cef19c7ff249dcd193b9039ff0c53d3e937ba40876ac

Observation 50d2822d-76db-470c-be92-a1858c3ec1a8 · outbound

This paper cites PowerSGD: Practical low-rank gradient compression for distributed optimization.Advances in Neural Information Processing Systems, 32, 2019.

Sketched Gaussian Mechanism for Private Federated Learning PowerSGD: Practical low-rank gradient compression for distributed optimization.Advances in Neural Information Processing Systems, 32, 2019

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:12:53.506443Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:12:52.752955Z digest=sha256:92b38349f52b8f07b7bce434200f2ce7d80f81c69e51474d037dde3b89c3a133

Observation 4d938735-70e9-4482-a18c-a2886ecacde3 · outbound

This paper cites SketchML: Accelerating distributed machine learning with data sketches.

Sketched Gaussian Mechanism for Private Federated Learning SketchML: Accelerating distributed machine learning with data sketches

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:12:53.494210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:12:52.756010Z digest=sha256:4d3543e9ced064b329f8b79a1f412e13b35f0c58446b10e9386ec401b50238ad

Observation 40a57b13-27ed-4d7c-bba4-2ae9b7704a70 · outbound

This paper cites Sparse Random Networks for Communication-Efficient Federated Learning.

Sketched Gaussian Mechanism for Private Federated Learning Sparse Random Networks for Communication-Efficient Federated Learning

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-04T21:12:52.759124Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T21:12:52.759124Z digest=sha256:40a6b457decb045a709fba7f99f3d34ef05c1e94a351185f7618115bd250d0e9

Observation 2ff1e93b-bfba-452d-9e99-fda5880eb099 · outbound

This paper cites LotteryFL: Personalized and Communication-Efficient Federated Learning with Lottery Ticket Hypothesis on Non-IID Datasets.

Sketched Gaussian Mechanism for Private Federated Learning LotteryFL: Personalized and Communication-Efficient Federated Learning with Lottery Ticket Hypothesis on Non-IID Datasets

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-04T21:12:52.762668Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T21:12:52.762668Z digest=sha256:5d5a178b0ccf6ae1def46865e337aeca2c51f8107434e2eda4bd85d1e1a6c357

Observation f71be9f4-2a10-4268-9d8b-0846251257c8 · outbound

This paper cites FedMask: Joint computation and communication-efficient personalized federated learning via heterogeneous masking.

Sketched Gaussian Mechanism for Private Federated Learning FedMask: Joint computation and communication-efficient personalized federated learning via heterogeneous masking

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:12:53.482074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:12:52.765889Z digest=sha256:974efbbb0819c620906b0a2348eaeaab8851103d86d837560aa6c4d8c99fa1ee

Observation 1f08b048-1df0-4432-8c19-1d433a5b0438 · outbound

This paper cites An improved data stream summary: the count-min sketch and its applications.Journal of Algorithms, 55(1):58–75, 2005.

Sketched Gaussian Mechanism for Private Federated Learning An improved data stream summary: the count-min sketch and its applications.Journal of Algorithms, 55(1):58–75, 2005

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:12:53.468395Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:12:52.768968Z digest=sha256:48d17fe3ce51c5974e59b3fe155df9fcd86a7cf7e62eb1d6d0278312c75bf65a

Observation 53d65609-cc8b-4d04-be56-558db50c47d7 · outbound

This paper cites Space-efficient online computation of quantile summaries.

Sketched Gaussian Mechanism for Private Federated Learning Space-efficient online computation of quantile summaries

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:12:53.454142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:12:52.771881Z digest=sha256:caacc532c18e34308a9fd93500244bc20803c590dff6d797fbaf5c2b4a2628e0

Observation 7892d047-8087-4ae9-820b-c77ac852c81e · outbound

This paper cites Kane and Jelani Nelson.

Sketched Gaussian Mechanism for Private Federated Learning Kane and Jelani Nelson

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:12:53.440396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:12:52.775116Z digest=sha256:f0969530801706e706a09041bc389f2a881a938de7883f47257c8e8bb21590a9

Observation e7d58e71-7f05-4f12-b451-ce2e4b7e5ceb · outbound

This paper cites Tropp, Alp Yurtsever, Madeleine Udell, and Volkan Cevher.

Sketched Gaussian Mechanism for Private Federated Learning Tropp, Alp Yurtsever, Madeleine Udell, and Volkan Cevher

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:12:53.429179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:12:52.777970Z digest=sha256:4b0e8c3dc5e2ab92c18485d0388238a4cde66a2e207e5532bfa2206e2762443c

Observation 74503705-96c3-42f3-ab3c-6196e7c35d15 · outbound

This paper cites Graph sketches: sparsification, spanners, and subgraphs.

Sketched Gaussian Mechanism for Private Federated Learning Graph sketches: sparsification, spanners, and subgraphs

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:12:53.416819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:12:52.780899Z digest=sha256:95990131d1d8864517ed4886a9ddb24ea67b2fe96cbe5241a8dd4bef8320ded7

Observation e6d4e0d0-08d3-46e8-be56-67e3dfcfb75a · outbound

This paper cites Asymptotics for sketching in least squares regression.Advances in Neural Information Processing Systems, 32, 2019.

Sketched Gaussian Mechanism for Private Federated Learning Asymptotics for sketching in least squares regression.Advances in Neural Information Processing Systems, 32, 2019

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:12:53.404506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:12:52.783883Z digest=sha256:f9eb1469ac05f04623f935527e370c34be150dfe21cea3ce2b562f7b6d2e6d80

Observation 6f31e1a6-5f4d-4dc3-857d-f42b2f85fc19 · outbound

This paper cites FedSKETCH: Communication-Efficient and Private Federated Learning via Sketching.

Sketched Gaussian Mechanism for Private Federated Learning FedSKETCH: Communication-Efficient and Private Federated Learning via Sketching

Reference 63

Resolution
verified exact
local_arxiv, observed 2026-08-04T21:12:52.964037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:12:52.786724Z digest=sha256:9f73100165116c6d34ffd474338ed1965c4d8220a2d17b5a5ec29bc779944949

Observation 52dae356-ef0f-42db-bb2b-6d162a7c9bcf · outbound

This paper cites Choquette-Choo, Peter Kairouz, and Ananda Theertha Suresh.

Sketched Gaussian Mechanism for Private Federated Learning Choquette-Choo, Peter Kairouz, and Ananda Theertha Suresh

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:12:53.391785Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:12:52.789854Z digest=sha256:1b1f0aa4b7ead3ed86f91dac0438ec2dfee025b09b124746a5150918e166d43a

Observation fc970a66-855f-4dc6-afd8-6ba293cb3c0f · outbound

This paper cites The algorithmic foundations of differential privacy.Foundations and Trends in Theoretical Computer Science, 9(3–4):211–407, 2014.

Sketched Gaussian Mechanism for Private Federated Learning The algorithmic foundations of differential privacy.Foundations and Trends in Theoretical Computer Science, 9(3–4):211–407, 2014

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:12:53.377510Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:12:52.793315Z digest=sha256:2d63780fa5fc32f4d03bb8d9943144aaaa913494b60002c614209af36d97725e

Observation 628aa69e-8ec8-4791-afdc-6dec62ec98d4 · outbound

This paper cites Yang, Farhad Farokhi, Shi Jin, Tony Q.

Sketched Gaussian Mechanism for Private Federated Learning Yang, Farhad Farokhi, Shi Jin, Tony Q

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:12:53.364130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:12:52.796509Z digest=sha256:89fc9a8615a79d727fac6758a200d1cbc55808639079c9a8c53486e850de9166

Observation fb5f5a17-d792-4b09-8437-d6c8856f5685 · outbound

This paper cites Brendan McMahan, Sar- var Patel, Daniel Ramage, Aaron Segal, and Karn Seth.

Sketched Gaussian Mechanism for Private Federated Learning Brendan McMahan, Sar- var Patel, Daniel Ramage, Aaron Segal, and Karn Seth

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:12:53.347032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:12:52.799802Z digest=sha256:ba4de91298d5123fd3619a37ff355674cd70831dd326d1dc8f3b04288a3d59ba

Observation 99b48097-43e6-498a-8049-cf18632bc88a · outbound

This paper cites 1-bit stochastic gradient descent and its application to data-parallel distributed training of speech DNNs.

Sketched Gaussian Mechanism for Private Federated Learning 1-bit stochastic gradient descent and its application to data-parallel distributed training of speech DNNs

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:12:53.333917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:12:52.803288Z digest=sha256:f533e624cd33ec387cd37e88b99a918489d30522730aaf078a76a8e48a156197

Observation 18f14081-342f-486b-965a-0e7d4babc3d3 · outbound

This paper cites An elementary proof of a theorem of Johnson and Linden- strauss.Random Structures & Algorithms, 22(1):60–65, 2003.

Sketched Gaussian Mechanism for Private Federated Learning An elementary proof of a theorem of Johnson and Linden- strauss.Random Structures & Algorithms, 22(1):60–65, 2003

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:12:53.321714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:12:52.806545Z digest=sha256:37a0a484be4ebd4f9e6b2fa60b01d9524dfec6860d323991331df52f54689e44

Observation 523aa17d-afe3-4b7b-b2a1-aff49b877134 · outbound

This paper cites Group normalization.

Sketched Gaussian Mechanism for Private Federated Learning Group normalization

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:12:53.308244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:12:52.809473Z digest=sha256:15f819e327af3cfa81b9e662295de1183bfc8474ce385dcdbc7fcd0664df162c

Observation 8a1fbd06-7620-43d9-a841-3815c0731771 · outbound

This paper cites an unresolved cited work.

Sketched Gaussian Mechanism for Private Federated Learning Unresolved cited work

Reference 71

Resolution
unresolved
raw_fallback, observed 2026-08-04T21:12:53.293834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation b172e0fb-80ea-4e55-ab32-887659c79ede · outbound

This paper cites Adaptive subgradient methods for online learning and stochastic optimization.Journal of Machine Learning Research, 12(7), 2011.

Sketched Gaussian Mechanism for Private Federated Learning Adaptive subgradient methods for online learning and stochastic optimization.Journal of Machine Learning Research, 12(7), 2011

Reference 72

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unresolved
no resolver link, observed 2026-08-04T21:12:52.815709Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T21:12:52.815709Z digest=sha256:53bb4d5d528447d89dfd927bb5fc237b53a545be342e2c1673c1b5e280c7f359

Observation 1e6ab9db-ba45-406c-a82a-f3680c9224c9 · outbound

This paper cites Divide the gradient by a running average of its recent magni- tude.

Sketched Gaussian Mechanism for Private Federated Learning Divide the gradient by a running average of its recent magni- tude

Reference 73

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verified fuzzy
raw_fallback, observed 2026-08-04T21:12:53.265923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:12:52.818551Z digest=sha256:b1bf2e0ce4fa2422781e00fd69c1f961115f4f4b3a6b455ba43fde605d87b78e

Observation dae07019-ae4f-40f9-a7ae-bf754d0a9148 · outbound

This paper cites ADADELTA: An Adaptive Learning Rate Method.

Sketched Gaussian Mechanism for Private Federated Learning ADADELTA: An Adaptive Learning Rate Method

Reference 74

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unresolved
no resolver link, observed 2026-08-04T21:12:52.821331Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T21:12:52.821331Z digest=sha256:225f47b8a0581a8d4a91b9268d995d8f8832ebdce0adb758e959737c791d5638

Observation e6750a05-ddb7-46f3-914a-e06c17246a11 · outbound

This paper cites Adaptive Gradient Methods with Dynamic Bound of Learning Rate.

Sketched Gaussian Mechanism for Private Federated Learning Adaptive Gradient Methods with Dynamic Bound of Learning Rate

Reference 75

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unresolved
no resolver link, observed 2026-08-04T21:12:52.824549Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T21:12:52.824549Z digest=sha256:7838a0ddc4ed231883aa69ecf1c359769b5ccf63fb08276fd7e709ae49038151

Observation b6a6243d-b713-499a-b08f-6f25bd7b456a · outbound

This paper cites Adaptive Federated Optimization.

Sketched Gaussian Mechanism for Private Federated Learning Adaptive Federated Optimization

Reference 76

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unresolved
no resolver link, observed 2026-08-04T21:12:52.827626Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T21:12:52.827626Z digest=sha256:361a176d2786a339a8a6914204726362a9c86aea40a5128d56dcc9914805452a

Observation 7ac90d1f-ecf3-4e26-ba97-3b1059588aee · outbound

This paper cites R ´enyi differential privacy.

Sketched Gaussian Mechanism for Private Federated Learning R ´enyi differential privacy

Reference 77

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verified fuzzy
raw_fallback, observed 2026-08-04T21:12:53.253806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:12:52.830689Z digest=sha256:4180c3945a8bf303c9e3cd4b274ad20bba09317aa6d905e2c65056ede86e0668

Observation 28112a80-d482-4b37-89cc-b70dd5ef4ecc · outbound

This paper cites Privacy for Free: Communication-Efficient Learning with Differential Privacy Using Sketches.

Sketched Gaussian Mechanism for Private Federated Learning Privacy for Free: Communication-Efficient Learning with Differential Privacy Using Sketches

Reference 78

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verified exact
local_arxiv, observed 2026-08-04T21:12:52.918559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:12:52.833619Z digest=sha256:28e20df01a8c156287e1c8b6a3c494a38e3f060287fd58567a38f2d5a24ce044

Observation 1f027e3a-f9ad-4637-bc5f-05bdd3f08a79 · outbound

This paper cites On measures of entropy and information.

Sketched Gaussian Mechanism for Private Federated Learning On measures of entropy and information

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:12:53.240687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:12:52.837071Z digest=sha256:f3eb5fc2bc8b08d2e41ae737e14773e6e4b4136c6b5d965db7eff5002b2e59b9

Observation 3d59527d-6e90-4341-b107-29026be99673 · outbound

This paper cites an unresolved cited work.

Sketched Gaussian Mechanism for Private Federated Learning Unresolved cited work

Reference 80

Resolution
unresolved
raw_fallback, observed 2026-08-04T21:12:53.227685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:12:52.840175Z digest=sha256:9b24fd66f41bbdb1349dcbcde2a4ea3b851029c296cb872762a5a1e2b20b9f15

Observation da102f70-0ff1-4631-9df3-e662c8652678 · outbound

This paper cites GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding.

Sketched Gaussian Mechanism for Private Federated Learning GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding

Reference 81

Resolution
unresolved
no resolver link, observed 2026-08-04T21:12:52.843063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T21:12:52.843063Z digest=sha256:39402e14edb60e54fb72d307fc185df16dc44c65c5375a94609c4ccc315e3c98

Observation 502791fa-0dd0-4087-a976-4125e09cbae8 · outbound

This paper cites BERT: Pre-training of deep bidirectional transformers for language understanding.

Sketched Gaussian Mechanism for Private Federated Learning BERT: Pre-training of deep bidirectional transformers for language understanding

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:12:53.213045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:12:52.846287Z digest=sha256:cdd574393f9265eca5937231a6de8ad224595fbf528aa078e18ec35fb99f04b6

Observation b89d0893-f0a7-476d-9449-9cb8fe6fc7e7 · outbound

This paper cites Efficient Private Statistics with Succinct Sketches.

Sketched Gaussian Mechanism for Private Federated Learning Efficient Private Statistics with Succinct Sketches

Reference 83

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unresolved
no resolver link, observed 2026-08-04T21:12:52.849424Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T21:12:52.849424Z digest=sha256:bba61f44a44564d59480ff99edda66264699c674972501be0aecd94e98739b3e

Observation 9cfe8cd4-b196-454e-b83c-bf009d1fa298 · outbound

This paper cites Federated heavy hitters discovery with differential privacy.

Sketched Gaussian Mechanism for Private Federated Learning Federated heavy hitters discovery with differential privacy

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:12:53.197527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:12:52.852628Z digest=sha256:c0b7d0a01eedec21b89baf5cbdd6ddc1aa2d291fa1a75159af69829a11d1bf43

Observation f05d994b-91e4-4fb8-b76d-aad2dc4e8ec9 · outbound

This paper cites ηlocal N X c∈Ct R⊤ t Rtclip ∆c,t ηlocal , τ +R ⊤ t zc,t # i ≤ √1−β 2ηlocal N ϵ2 X c∈Ct R⊤ t Rtclip ∆c,t ηlocal , τ i + √1−β 2ηlocal N ϵ2.

Sketched Gaussian Mechanism for Private Federated Learning ηlocal N X c∈Ct R⊤ t Rtclip ∆c,t ηlocal , τ +R ⊤ t zc,t # i ≤ √1−β 2ηlocal N ϵ2 X c∈Ct R⊤ t Rtclip ∆c,t ηlocal , τ i + √1−β 2ηlocal N ϵ2

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:12:53.185685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-04T21:12:52.855661Z digest=sha256:9e2e554d3d76a2a33649a34380e7d38634dae69c6d28df0addcbe601d3d0d41d

Pith citing papers

No inbound Pith citation observations are available.