Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
A Randomised Subspace Gauss-Newton Method for Nonlinear Least-Squares
As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2211.05727.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T19:54:41.525956Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-16T17:23:09.932876Z
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 3b77e9b7-b7c8-44be-aff9-7734dd1c77ba · inbound
Random Subspace Cubic-Regularization Methods, with Applications to Low-Rank Functions cites this paper.
Random Subspace Cubic-Regularization Methods, with Applications to Low-Rank Functions A Randomised Subspace Gauss-Newton Method for Nonlinear Least-Squares
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T19:54:41.525956Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b5ac8327-ab42-4e3a-8af9-bebf81c127a0 · inbound
A variable dimension sketching strategy for nonlinear least-squares cites this paper.
A variable dimension sketching strategy for nonlinear least-squares A Randomised Subspace Gauss-Newton Method for Nonlinear Least-Squares
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T10:58:26.126161Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d03e4d1b-5296-4ac9-a869-c6a00531338d · inbound
Monotone and nonmonotone linearized block coordinate descent methods for nonsmooth composite optimization problems cites this paper.
Monotone and nonmonotone linearized block coordinate descent methods for nonsmooth composite optimization problems A Randomised Subspace Gauss-Newton Method for Nonlinear Least-Squares
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T01:04:12.451746Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4744d7c8-ca1a-495c-93d5-f2aa57307284 · inbound
Model-Driven Subspaces for Large-Scale Optimization with Local Approximation Strategy cites this paper.
Model-Driven Subspaces for Large-Scale Optimization with Local Approximation Strategy A Randomised Subspace Gauss-Newton Method for Nonlinear Least-Squares
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T21:04:57.157152Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3b1d3fc1-fc4a-4d28-80af-e6f7cfb29a93 · inbound
On the Convergence Behavior of Preconditioned Gradient Descent Toward the Rich Learning Regime cites this paper.
On the Convergence Behavior of Preconditioned Gradient Descent Toward the Rich Learning Regime A Randomised Subspace Gauss-Newton Method for Nonlinear Least-Squares
Reference 5
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T17:23:09.936752Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.