Paper Citation Record · LEDGER

Incremental Methods for Weakly Convex Optimization

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:1907.11687.

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

pith.paper-citation-record.v1
1907.11687 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T10:45:07.175028Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T02:23:31.774978Z

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 f854c36d-00df-4614-bbe6-50cabc926e89 · inbound

A Nonconvex Approach for Exact and Efficient Multichannel Sparse Blind Deconvolution cites this paper.

A Nonconvex Approach for Exact and Efficient Multichannel Sparse Blind Deconvolution Incremental Methods for Weakly Convex Optimization

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-14T10:45:07.175028Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9afae420-f153-4eda-b9dd-847475b27e49 · inbound

Improved Last-Iterate Convergence of Shuffling Gradient Methods for Nonsmooth Convex Optimization cites this paper.

Improved Last-Iterate Convergence of Shuffling Gradient Methods for Nonsmooth Convex Optimization Incremental Methods for Weakly Convex Optimization

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-07T13:07:43.671793Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 261f352a-a28d-4ceb-9e1f-f7d823185904 · inbound

A Proximal Variable Smoothing for Minimization of Nonlinearly Composite Nonsmooth Function -- Finite-Max Minimization and MIMO Applications cites this paper.

A Proximal Variable Smoothing for Minimization of Nonlinearly Composite Nonsmooth Function -- Finite-Max Minimization and MIMO Applications Incremental Methods for Weakly Convex Optimization

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T10:24:39.405994Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3e76d2e4-86b6-4c77-9b3a-4f3524aef867 · inbound

Convergence of difference inclusions via a diameter criterion cites this paper.

Convergence of difference inclusions via a diameter criterion Incremental Methods for Weakly Convex Optimization

Reference 300

Resolution: verified exact; arxiv_id, observed 2026-05-15T02:23:31.777638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.