Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Linearly convergent stochastic heavy ball method for minimizing generalization error
As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1710.10737.
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 2026-08-04T06:34:03.388597+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-07-11T20:46:05.467029Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-05-24T17:59:46.465633Z
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 3aa25c51-3885-49a1-942f-4aedc3b04eea · inbound
Heavy-ball Algorithms Always Escape Saddle Points cites this paper.
Heavy-ball Algorithms Always Escape Saddle Points Linearly convergent stochastic heavy ball method for minimizing generalization error
Reference 17
- Resolution
- verified exact
- local_arxiv, observed 2026-05-24T17:59:46.468560Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation a25085a6-0316-4c9f-9275-69cdf5597e6a · inbound
Perfect Parallelization in Mini-Batch SGD with Classical Momentum Acceleration cites this paper.
Perfect Parallelization in Mini-Batch SGD with Classical Momentum Acceleration Linearly convergent stochastic heavy ball method for minimizing generalization error
Reference 36
- Resolution
- verified exact
- local_arxiv, observed 2026-05-20T12:28:17.180026Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 90d02765-22d1-4953-b944-5586cb926325 · inbound
Unified convergence analysis for gradient descent optimization methods in the training of deep neural networks cites this paper.
Unified convergence analysis for gradient descent optimization methods in the training of deep neural networks Linearly convergent stochastic heavy ball method for minimizing generalization error
Reference 45
- Resolution
- unresolved
- no resolver link, observed 2026-07-11T20:46:05.467029Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.