Pith. sign in

Paper Citation Record · LEDGER

The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches

As of 9 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 1 inbound Pith citation observation for arXiv:2505.24603.

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

pith.paper-citation-record.v1
2505.24603 v2

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:31:57.698155Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-09T16:02:19.749100Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

18 of 18 outbound references displayed

  • verified exact0
  • verified fuzzy13
  • unresolved4
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 0d471baf-75ef-4463-9335-e6227959fc51 · outbound

This paper cites (5) For an invertible matrix A, we have [Brookes, 2020, Section.

The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches (5) For an invertible matrix A, we have [Brookes, 2020, Section

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:31:59.187523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:31:57.014477Z digest=sha256:502bbe5c6369cb141cf9f53383e724f52af9c89c0ff1df177df2564c1ac50dcf

Observation aa0417dd-a2e7-4a6b-8cc5-f2ac7e099564 · outbound

This paper cites Our second baseline, from Sheffet [2017, Algorithm 1], was implemented according to the description in Appendix H.2.

The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches Our second baseline, from Sheffet [2017, Algorithm 1], was implemented according to the description in Appendix H.2

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:31:58.514120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:31:57.457109Z digest=sha256:dd77fee0817591a0f4686e7b2498f8a46c5441040e95ff0c5fc1aefb947c526b

Observation 734a4c28-4f1b-4778-abab-a328c21d8c5d · outbound

This paper cites 1, Sheffet '17]: k d = 2.500 ADASSP [Wang '18] [Alg.

The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches 1, Sheffet '17]: k d = 2.500 ADASSP [Wang '18] [Alg

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:31:58.114719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:31:57.698155Z digest=sha256:6989e62554ecb56597f2ec0e6521fb30d8c8c297bde2ada039ff99b101dbab89

Observation f1c2e91e-c0d0-4faa-8561-4fc6b37984ad · outbound

This paper cites an unresolved cited work.

The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches Unresolved cited work

Reference 9

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:31:59.353603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:31:56.914296Z digest=sha256:e35e942f007c5687d73758278211bf3d2848aa8cd3093ffe14e413bd4b7ac890

Observation 01153b25-38a5-4d03-a0b9-99af0166c681 · outbound

This paper cites We define the discriminant to be ∆H = 1 + 2γ + γ2 log 1 − 1 γ 2 − 8γ 1 + γ + γ2 log 1 − 1 γ which is non-negative.

The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches We define the discriminant to be ∆H = 1 + 2γ + γ2 log 1 − 1 γ 2 − 8γ 1 + γ + γ2 log 1 − 1 γ which is non-negative

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:31:59.059272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:31:57.084978Z digest=sha256:9799690c1768bee0794cfb63427f816fbb66cf628e182006e09e386cd1294ffc

Observation 76ec1e86-c8d8-4766-90fa-a9e607b1cb8c · outbound

This paper cites The first case (when γ ≤ τ ) trivially satisfies this.

The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches The first case (when γ ≤ τ ) trivially satisfies this

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:31:58.866486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:31:57.155546Z digest=sha256:51f3180d1e91731193bc4e49b74f2ded565ae2b3e7cad5ae4f1b008b4ac51148

Observation 098f79fd-9113-49ed-b9fb-3d3430538d1b · outbound

This paper cites H Algorithms: Linear Regression H.1 AdaSSP Algorithm 3 AdaSSP [Wang, 2018] Input: Dataset (X, Y); Privacy parameters ε, δ; Bounds: max i∈[n] ∥xi∥2 ≤ C2 X , max i∈[n] |yi|2 ≤ C2 Y.

The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches H Algorithms: Linear Regression H.1 AdaSSP Algorithm 3 AdaSSP [Wang, 2018] Input: Dataset (X, Y); Privacy parameters ε, δ; Bounds: max i∈[n] ∥xi∥2 ≤ C2 X , max i∈[n] |yi|2 ≤ C2 Y

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:31:58.747142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:31:57.273530Z digest=sha256:4ae2bc595dff12a84b38077f8fde917becdaf72dc78c6facb56a7cc1edee4a56

Observation 047cfbc4-6e81-4aa8-b0bf-e421a056c134 · outbound

This paper cites 1: Compute λmin := λmin((X, Y)⊤(X, Y)).

The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches 1: Compute λmin := λmin((X, Y)⊤(X, Y))

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:31:58.672901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:31:57.367675Z digest=sha256:cebf59fcf5c28e1aa3b5762dee8a085a943f80d5dabce29b2b3bac19d9d2f006

Observation b879662d-2343-41e1-bc28-aef2b1ef8a87 · outbound

This paper cites The train and test loaders were generated using torch.utils.data.DataLoader with shuffling enabled.

The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches The train and test loaders were generated using torch.utils.data.DataLoader with shuffling enabled

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:31:58.394176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:31:57.557315Z digest=sha256:e6f171e3c0d4dce29e07487a37c7c32edf21d136db576a8a6cc5718adfe43a62

Observation dda57975-7027-48d7-aed0-089dde8aaaa5 · outbound

This paper cites Runtime comparisons show the ratio of execution times for the largest simulated ε.

The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches Runtime comparisons show the ratio of execution times for the largest simulated ε

Reference 500

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:31:58.282853Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:31:57.611960Z digest=sha256:110f7867135187075e7c06f8f479bc09b3b3eb083236d25a4c774d213d4542f4

Observation 206ff287-f1af-41ae-9f71-2a3bd60e640c · outbound

This paper cites Improved approximation algorithms for large matrices via random projections.

The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches Improved approximation algorithms for large matrices via random projections

Reference 1961

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:31:59.610056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:31:56.343762Z digest=sha256:461a0950c048023d51c2c5db717ef30ac97db7d21b30bad1e2eeabd87a82324c

Observation 18eaef21-b582-429c-bc96-185300c1478f · outbound

This paper cites Private Approximations of the 2nd-Moment Matrix Using Existing Techniques in Linear Regression.

The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches Private Approximations of the 2nd-Moment Matrix Using Existing Techniques in Linear Regression

Reference 2006

Resolution
unresolved
no resolver link, observed 2026-08-07T12:31:56.571254Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:31:56.571254Z digest=sha256:5a8f42de1b0186a56be1425023b8e6d8530eb3e6c649316017cdea4071ea36ca

Observation b2d81ec5-8e9d-4036-bfe9-4a0c9089839c · outbound

This paper cites edu/~kriz/learning-features-2009-TR.pdf.

The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches edu/~kriz/learning-features-2009-TR.pdf

Reference 2009

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:31:59.718160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:31:56.257263Z digest=sha256:a7aff0bc24fb3a3ab0dd5b9caf40f245cf8f7810729c81ff5332ca8d2024b516

Observation ca16415d-1375-40b5-8f97-5f153adf7dfa · outbound

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

The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

Reference 2014

Resolution
unresolved
no resolver link, observed 2026-08-07T12:31:56.747036Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:31:56.747036Z digest=sha256:0267a807af1e93f40a84f56f11bcea6b9b10f3ea76391134679b51f8a24edd73

Observation 8a782b08-c043-4001-a549-aa508a3e5f12 · outbound

This paper cites Opacus: User-Friendly Differential Privacy Library in PyTorch.

The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches Opacus: User-Friendly Differential Privacy Library in PyTorch

Reference 2017

Resolution
unresolved
no resolver link, observed 2026-08-07T12:31:56.839268Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:31:56.839268Z digest=sha256:8b70a4f0a1c27d218d07dd349221ccc981378fa9cbad94d646e5b06ca930a16c

Observation 4a5d52e0-188e-418d-9a3e-135870c17f81 · outbound

This paper cites A History of Census Privacy Protections.

The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches A History of Census Privacy Protections

Reference 2018

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:31:59.821538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:31:56.096909Z digest=sha256:d07eac794595e725d56b03d9dbecdf4518d0912b138171fb37202dda9f58a1ef

Observation 0bf8d54e-483c-48f4-9483-3ee7ab31b65a · outbound

This paper cites Private Regression via Data-Dependent Sufficient Statistic Perturbation.

The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches Private Regression via Data-Dependent Sufficient Statistic Perturbation

Reference 2020

Resolution
metadata mismatch
local_arxiv, observed 2026-08-07T12:31:57.979546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:31:56.163962Z digest=sha256:2b2277550b95ef42179c0dc9f4c701d690522f04465f0d80017260c1334cc893

Observation bac6eb0c-13f5-44d5-8ded-60858f493e67 · outbound

This paper cites Yuchang Sun, Jiawei Shao, Songze Li, Yuyi Mao, and Jun Zhang.

The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches Yuchang Sun, Jiawei Shao, Songze Li, Yuyi Mao, and Jun Zhang

Reference 2022

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:31:59.457278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:31:56.653847Z digest=sha256:1cdc19db04a3c68b4a5d4f1ba73cf2397f1a064c113673f075441cd84ad17977

Pith citing papers

Observation c0c7d6b5-cd30-40f3-9191-9c775c7045fa · inbound

Quadratic Objective Perturbation: Curvature-Based Differential Privacy cites this paper.

Quadratic Objective Perturbation: Curvature-Based Differential Privacy The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-05-09T21:58:47.171884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-09T16:02:19.749100Z digest=sha256:310252285c821073703a13bcb801035531d270a92cc56d50b754f771f3bf6606