Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T12:31:57.698155Z
Paper Citation Record · LEDGER
As of 7 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.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T12:31:57.698155Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-09T16:02:19.749100Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
18 of 18 outbound references displayed
External citation measurements
0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Observation 0d471baf-75ef-4463-9335-e6227959fc51 · outbound
The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches (5) For an invertible matrix A, we have [Brookes, 2020, Section
Reference 1
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation aa0417dd-a2e7-4a6b-8cc5-f2ac7e099564 · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 734a4c28-4f1b-4778-abab-a328c21d8c5d · outbound
The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches 1, Sheffet '17]: k d = 2.500 ADASSP [Wang '18] [Alg
Reference 4
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation f1c2e91e-c0d0-4faa-8561-4fc6b37984ad · outbound
The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches Unresolved cited work
Reference 9
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 01153b25-38a5-4d03-a0b9-99af0166c681 · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 76ec1e86-c8d8-4766-90fa-a9e607b1cb8c · outbound
The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches The first case (when γ ≤ τ ) trivially satisfies this
Reference 12
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 098f79fd-9113-49ed-b9fb-3d3430538d1b · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 047cfbc4-6e81-4aa8-b0bf-e421a056c134 · outbound
The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches 1: Compute λmin := λmin((X, Y)⊤(X, Y))
Reference 14
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation b879662d-2343-41e1-bc28-aef2b1ef8a87 · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation dda57975-7027-48d7-aed0-089dde8aaaa5 · outbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 206ff287-f1af-41ae-9f71-2a3bd60e640c · outbound
The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches Improved approximation algorithms for large matrices via random projections
Reference 1961
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 18eaef21-b582-429c-bc96-185300c1478f · outbound
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b2d81ec5-8e9d-4036-bfe9-4a0c9089839c · outbound
The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches edu/~kriz/learning-features-2009-TR.pdf
Reference 2009
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation ca16415d-1375-40b5-8f97-5f153adf7dfa · outbound
The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms
Reference 2014
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8a782b08-c043-4001-a549-aa508a3e5f12 · outbound
The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches Opacus: User-Friendly Differential Privacy Library in PyTorch
Reference 2017
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4a5d52e0-188e-418d-9a3e-135870c17f81 · outbound
The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches A History of Census Privacy Protections
Reference 2018
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 0bf8d54e-483c-48f4-9483-3ee7ab31b65a · outbound
The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches Private Regression via Data-Dependent Sufficient Statistic Perturbation
Reference 2020
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation bac6eb0c-13f5-44d5-8ded-60858f493e67 · outbound
The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches Yuchang Sun, Jiawei Shao, Songze Li, Yuyi Mao, and Jun Zhang
Reference 2022
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation c0c7d6b5-cd30-40f3-9191-9c775c7045fa · inbound
Quadratic Objective Perturbation: Curvature-Based Differential Privacy The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches
Reference 34
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.