Paper Citation Record · LEDGER

A Short Note on Concentration Inequalities for Random Vectors with SubGaussian Norm

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 18 inbound Pith citation observations for arXiv:1902.03736.

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

pith.paper-citation-record.v1
1902.03736 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 18 of 18 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T23:21:23.970314Z

measured 1 of 1 external citation measurements

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

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

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
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malformed identifier0
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External citation measurements

75
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 146ff183-68b5-4b2a-aa2b-6a8d60db0ad3 · inbound

Isoperimetry is All We Need: Langevin Posterior Sampling for RL with Sublinear Regret cites this paper.

Isoperimetry is All We Need: Langevin Posterior Sampling for RL with Sublinear Regret A Short Note on Concentration Inequalities for Random Vectors with SubGaussian Norm

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-10T23:21:23.970314Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d37251d-3a48-4174-b2df-a757c5861732 · inbound

Online Covariance Estimation in Nonsmooth Stochastic Approximation cites this paper.

Online Covariance Estimation in Nonsmooth Stochastic Approximation A Short Note on Concentration Inequalities for Random Vectors with SubGaussian Norm

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-08T19:59:24.292143Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e78d2b6-b12d-47d4-9753-31ad6b599935 · inbound

Linear-Time User-Level DP-SCO via Robust Statistics cites this paper.

Linear-Time User-Level DP-SCO via Robust Statistics A Short Note on Concentration Inequalities for Random Vectors with SubGaussian Norm

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T23:32:14.073211Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c0270d7c-c03b-4f72-845b-d59b8b71296d · inbound

Minimax Rate-Optimal Algorithms for High-Dimensional Stochastic Linear Bandits cites this paper.

Minimax Rate-Optimal Algorithms for High-Dimensional Stochastic Linear Bandits A Short Note on Concentration Inequalities for Random Vectors with SubGaussian Norm

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:42.498133Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d82fa76-ef21-41a1-8faa-86ef1e528634 · inbound

Privacy Amplification in Differentially Private Zeroth-Order Optimization with Hidden States cites this paper.

Privacy Amplification in Differentially Private Zeroth-Order Optimization with Hidden States A Short Note on Concentration Inequalities for Random Vectors with SubGaussian Norm

Reference 13

Resolution: metadata mismatch; local_arxiv, observed 2026-05-19T12:02:16.851855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4f9a1295-00b6-4acf-ae3d-7d9cf7e4cb19 · inbound

On the Benefits of Accelerated Optimization in Robust and Private Estimation cites this paper.

On the Benefits of Accelerated Optimization in Robust and Private Estimation A Short Note on Concentration Inequalities for Random Vectors with SubGaussian Norm

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T11:22:21.277330Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6e974a18-d907-4f71-9b52-9ec1857356fb · inbound

GL-LowPopArt: A Nearly Instance-Wise Minimax-Optimal Estimator for Generalized Low-Rank Trace Regression cites this paper.

GL-LowPopArt: A Nearly Instance-Wise Minimax-Optimal Estimator for Generalized Low-Rank Trace Regression A Short Note on Concentration Inequalities for Random Vectors with SubGaussian Norm

Reference 5

Resolution: metadata mismatch; local_arxiv, observed 2026-05-19T10:52:14.756680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d0d82ea8-7485-41af-949d-cdab21e83592 · inbound

GL-LowPopArt: A Nearly Instance-Wise Minimax-Optimal Estimator for Generalized Low-Rank Trace Regression cites this paper.

GL-LowPopArt: A Nearly Instance-Wise Minimax-Optimal Estimator for Generalized Low-Rank Trace Regression A Short Note on Concentration Inequalities for Random Vectors with SubGaussian Norm

Reference 6

Resolution: metadata mismatch; local_arxiv, observed 2026-05-19T10:52:14.738922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 803ec613-e2ad-4368-9dfb-79109d281e62 · inbound

Deviation Inequalities for R\'{e}nyi Divergence Estimators via Variational Expression cites this paper.

Deviation Inequalities for R\'{e}nyi Divergence Estimators via Variational Expression A Short Note on Concentration Inequalities for Random Vectors with SubGaussian Norm

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-05T21:16:50.978310Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b962733f-1cbb-4f94-b58f-a960baa298ba · inbound

High-Probability Convergence Guarantees of Decentralized SGD cites this paper.

High-Probability Convergence Guarantees of Decentralized SGD A Short Note on Concentration Inequalities for Random Vectors with SubGaussian Norm

Reference 76

Resolution: verified exact; local_arxiv, observed 2026-05-18T08:46:07.833862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1c23df03-e1a5-4900-8a67-bd6867ceb0e0 · inbound

High-Probability Convergence Guarantees of Decentralized SGD cites this paper.

High-Probability Convergence Guarantees of Decentralized SGD A Short Note on Concentration Inequalities for Random Vectors with SubGaussian Norm

Reference 76

Resolution: verified exact; local_arxiv, observed 2026-05-22T13:16:35.029746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 92472465-0d85-4f50-a1d6-689b6bd5a9e3 · inbound

Token Sample Complexity of Attention cites this paper.

Token Sample Complexity of Attention A Short Note on Concentration Inequalities for Random Vectors with SubGaussian Norm

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-03T17:10:08.606714Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3681709a-066b-401a-ba42-978a2ccce644 · inbound

On the Accuracy of Newton Step and Influence Function Data Attributions cites this paper.

On the Accuracy of Newton Step and Influence Function Data Attributions A Short Note on Concentration Inequalities for Random Vectors with SubGaussian Norm

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-05-21T17:50:26.336667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a7ec6c7f-8d8c-4f0c-8822-3e47bfdff851 · inbound

Limitations of SGD for Multi-Index Models Beyond Statistical Queries cites this paper.

Limitations of SGD for Multi-Index Models Beyond Statistical Queries A Short Note on Concentration Inequalities for Random Vectors with SubGaussian Norm

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-03T04:19:44.875137Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f94ba06f-7da6-455f-b7d6-1bba66c7dd80 · inbound

An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness cites this paper.

An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness A Short Note on Concentration Inequalities for Random Vectors with SubGaussian Norm

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-04T06:00:14.440596Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d4960b56-2a9a-439a-a8c1-5f13608c4901 · inbound

Concentration of General Stochastic Approximation Under Heavy-Tailed Markovian Noise cites this paper.

Concentration of General Stochastic Approximation Under Heavy-Tailed Markovian Noise A Short Note on Concentration Inequalities for Random Vectors with SubGaussian Norm

Reference 21

Resolution: metadata mismatch; local_arxiv, observed 2026-05-21T02:29:25.114037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c5acdb43-3d66-4fb7-be00-95e201f2d3e6 · inbound

Non-Asymptotic Convergence of Stochastic Iterative Algorithms: A Lyapunov Framework cites this paper.

Non-Asymptotic Convergence of Stochastic Iterative Algorithms: A Lyapunov Framework A Short Note on Concentration Inequalities for Random Vectors with SubGaussian Norm

Reference 60

Resolution: verified exact; local_arxiv, observed 2026-06-28T23:12:46.679836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0d3bfb3c-7321-406e-85a0-253fb537ccf5 · inbound

Near-Optimal Pure Machine Unlearning for Smooth Strongly Convex Losses cites this paper.

Near-Optimal Pure Machine Unlearning for Smooth Strongly Convex Losses A Short Note on Concentration Inequalities for Random Vectors with SubGaussian Norm

Reference 7

Resolution: metadata mismatch; local_arxiv, observed 2026-07-01T22:06:15.773768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.