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Paper Citation Record · LEDGER

Exact convergence rate of the last iterate in subgradient methods

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2307.11134.

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

pith.paper-citation-record.v1
2307.11134 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:42:48.196514Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T04:37:36.542213Z

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 2f978e0e-a9be-465e-912e-cdc667bda462 · inbound

Training Deep Learning Models with Norm-Constrained LMOs cites this paper.

Training Deep Learning Models with Norm-Constrained LMOs Exact convergence rate of the last iterate in subgradient methods

Reference 219

Resolution
verified exact
arxiv_id, observed 2026-05-21T21:22:37.168853Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-21T21:22:36.870292Z digest=sha256:512f17d34338f77b2cfbd81751990eb9d7e5d6b3533fd471f2051535b268d4ec

Observation 24a51a21-9221-4c02-addb-0ecc48c4b659 · inbound

Optimized methods for composite optimization: a reduction perspective cites this paper.

Optimized methods for composite optimization: a reduction perspective Exact convergence rate of the last iterate in subgradient methods

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-06T21:42:48.196514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:42:48.196514Z digest=sha256:6f51548d16aca8ef5afca4ebf9623d6ec591dfda75c30ec18e321633ad641cad

Observation ece026e4-ea3e-4ee6-a703-85f01bb98c32 · inbound

Fast Last-Iterate Convergence of SGD in the Smooth Interpolation Regime cites this paper.

Fast Last-Iterate Convergence of SGD in the Smooth Interpolation Regime Exact convergence rate of the last iterate in subgradient methods

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-06T17:26:08.763414Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T17:26:08.763414Z digest=sha256:6034d5489e5d0b86a67cadc46362a131c42db6db5661ffed218fa1f20e8ed34c

Observation 21fb4db9-beaf-4fe6-be07-a0986dc2ac29 · inbound

Last-Iterate Complexity of SGD for Convex and Smooth Stochastic Problems cites this paper.

Last-Iterate Complexity of SGD for Convex and Smooth Stochastic Problems Exact convergence rate of the last iterate in subgradient methods

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-06T16:19:03.602887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:19:03.602887Z digest=sha256:6468c7f2ed4f44ea2e823a42c6e1073e158457218dc9754f847027a2cbde18fd

Observation 90df7d6c-f675-451f-a912-b49bbdbd2f20 · inbound

Gradient Descent's Last Iterate is Often (slightly) Suboptimal cites this paper.

Gradient Descent's Last Iterate is Often (slightly) Suboptimal Exact convergence rate of the last iterate in subgradient methods

Reference 29

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T12:30:23.747778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-10T12:27:10.934480Z digest=sha256:0c7da4f60d2ef921078c598cf729bbf7f53142ad2639e79b94ba327b671f1fad

Observation cc2c8ec3-bb3b-4c01-9169-2fb7b11d270a · inbound

Mirror Descent Beyond Euclidean Stability: An Exponential Separation in Initialization Sensitivity cites this paper.

Mirror Descent Beyond Euclidean Stability: An Exponential Separation in Initialization Sensitivity Exact convergence rate of the last iterate in subgradient methods

Reference 16

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T04:37:36.543966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-27T13:50:05.391989Z digest=sha256:a6551ac4b77d0c263a82a270c5661a24a95d3d6c4a8eb74ae98fd3a2faf29f8d

Observation c7b26d10-213c-471b-86c3-2813946e0fa6 · inbound

Convergence of Continual Learning in Homogeneous Deep Networks cites this paper.

Convergence of Continual Learning in Homogeneous Deep Networks Exact convergence rate of the last iterate in subgradient methods

Reference 27

Resolution
metadata mismatch
arxiv_id, observed 2026-06-30T07:14:21.731466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-30T07:05:09.767632Z digest=sha256:9c773feef474ef33c2eb3b61b459eec1718b53577d2dfa9f793f5f35cb0d5a1e