Paper Citation Record · LEDGER

Optimization for deep learning: theory and algorithms

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:1912.08957.

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

pith.paper-citation-record.v1
1912.08957 v1

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 2026-08-15T06:32:42.880941+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:11:06.954746Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T10:43:44.794782Z

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 a35a68bb-d5e5-4612-97aa-40bec71fbc9b · inbound

Averaged Adam accelerates stochastic optimization in the training of deep neural network approximations for partial differential equation and optimal control problems cites this paper.

Averaged Adam accelerates stochastic optimization in the training of deep neural network approximations for partial differential equation and optimal control problems Optimization for deep learning: theory and algorithms

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-10T21:11:06.954746Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 26fff830-1fc2-4193-a377-d46ca9e8f0c2 · inbound

Mathematical analysis of the gradients in deep learning cites this paper.

Mathematical analysis of the gradients in deep learning Optimization for deep learning: theory and algorithms

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-10T14:10:55.368199Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 78d20b1f-17a6-45ad-9640-859b7bedfddf · inbound

Bridging Jensen Gap for Max-Min Group Fairness Optimization in Recommendation cites this paper.

Bridging Jensen Gap for Max-Min Group Fairness Optimization in Recommendation Optimization for deep learning: theory and algorithms

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-07T22:00:38.463850Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 09673eaf-1bd1-4f24-9fed-59568c47a922 · inbound

DeePoly: A High-Order Accuracy Scientific Machine Learning Framework for Function Approximation and Solving PDEs cites this paper.

DeePoly: A High-Order Accuracy Scientific Machine Learning Framework for Function Approximation and Solving PDEs Optimization for deep learning: theory and algorithms

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-08-07T10:43:44.851511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.