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Paper Citation Record · LEDGER

Easy Differentially Private Linear Regression

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2208.07353.

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

pith.paper-citation-record.v1
2208.07353 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T15:30:21.995531Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T13:08:07.906323Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 867dd7d6-501c-4458-a349-23467a9fe471 · inbound

Improved subsample-and-aggregate via the private modified winsorized mean cites this paper.

Improved subsample-and-aggregate via the private modified winsorized mean Easy Differentially Private Linear Regression

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-10T15:30:21.995531Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T15:30:21.995531Z digest=sha256:ad7738bc7f1a7d7844aeedc17c79876aceb8ccf57dfefc587fa8450d182a7ec4

Observation 79d5abc4-1167-42c8-bba9-a960e2b4dc6c · inbound

Computational Attestations of Polynomial Integrity Towards Verifiable Machine-Learning cites this paper.

Computational Attestations of Polynomial Integrity Towards Verifiable Machine-Learning Easy Differentially Private Linear Regression

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-07T04:09:03.567716Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:09:03.567716Z digest=sha256:f3fa69436882bcaaa396272cb2d6a121c3a923ad3c57c9edfc612445ecf2f707

Observation e89ed99d-716f-4367-8284-7c94b33c8139 · inbound

Computationally tractable robust differentially private mean estimation cites this paper.

Computationally tractable robust differentially private mean estimation Easy Differentially Private Linear Regression

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-07-03T13:08:07.907877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-06-27T08:34:28.732765Z digest=sha256:7b21a226a321869e8b9b429c34af1bb5b52d9beee47d5e76f17bd6c8630d875e