Paper Citation Record · LEDGER

Linear Convergence of Adaptive Stochastic Gradient Descent

As of 22 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:1908.10525.

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

pith.paper-citation-record.v1
1908.10525 v2

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T10:47:31.432012Z

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

18 of 18 outbound references displayed

verified exact1
verified fuzzy2
unresolved15
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6ab720da-0006-41a2-8b13-bdf23c017ba5 · outbound

This paper cites (2018): F (xk0−1) ≤ F (x0) + η2L 2 (1 + log( b2 k0−1 b2 0 )).

Linear Convergence of Adaptive Stochastic Gradient Descent (2018): F (xk0−1) ≤ F (x0) + η2L 2 (1 + log( b2 k0−1 b2 0 ))

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:47:31.747751Z

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.

Observation 8eb866e5-a1fe-4b43-9a4c-f99af31a8853 · outbound

This paper cites However, after tuning η = 10000 in stochastic setting and η = 100 in batch setting, the convergence rate of AdaGrad-Norm is better again.

Linear Convergence of Adaptive Stochastic Gradient Descent However, after tuning η = 10000 in stochastic setting and η = 100 in batch setting, the convergence rate of AdaGrad-Norm is better again

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:47:31.731828Z

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.

Observation 4b273839-6338-4422-83f8-afdb1f0a4925 · outbound

This paper cites an unresolved cited work.

Linear Convergence of Adaptive Stochastic Gradient Descent Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-08-14T10:47:31.715509Z

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.

Observation 4c03a4da-f398-43b0-a21e-c62c94452a9d · outbound

This paper cites A Sufficient Condition for Convergences of Adam and RMSProp.

Linear Convergence of Adaptive Stochastic Gradient Descent A Sufficient Condition for Convergences of Adam and RMSProp

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-14T10:47:31.375228Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 904dc547-dc3b-4335-a6f3-35741be8a6b3 · outbound

This paper cites AdaGrad stepsizes: Sharp convergence over nonconvex landscapes.

Linear Convergence of Adaptive Stochastic Gradient Descent AdaGrad stepsizes: Sharp convergence over nonconvex landscapes

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-14T10:47:31.380155Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation be367608-7198-49ba-b812-13d0d7321d36 · outbound

This paper cites WNGrad: Learn the Learning Rate in Gradient Descent.

Linear Convergence of Adaptive Stochastic Gradient Descent WNGrad: Learn the Learning Rate in Gradient Descent

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-14T10:47:31.385502Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f6db588b-1399-4e02-9f65-f0dcd41ac1df · outbound

This paper cites On the Convergence of Stochastic Gradient Descent with Adaptive Stepsizes.

Linear Convergence of Adaptive Stochastic Gradient Descent On the Convergence of Stochastic Gradient Descent with Adaptive Stepsizes

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-14T10:47:31.390275Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca916c6b-dc1e-4797-849b-39e7af5b864d · outbound

This paper cites Fast and Faster Convergence of SGD for Over-Parameterized Models and an Accelerated Perceptron.

Linear Convergence of Adaptive Stochastic Gradient Descent Fast and Faster Convergence of SGD for Over-Parameterized Models and an Accelerated Perceptron

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-14T10:47:31.394878Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d50a180f-be27-4024-9110-15c9ec01e24b · outbound

This paper cites Understanding deep learning requires rethinking generalization.

Linear Convergence of Adaptive Stochastic Gradient Descent Understanding deep learning requires rethinking generalization

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-14T10:47:31.401412Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4fb55d86-6a6a-4bb4-af75-616871783ff7 · outbound

This paper cites Fast Convergence of Stochastic Gradient Descent under a Strong Growth Condition.

Linear Convergence of Adaptive Stochastic Gradient Descent Fast Convergence of Stochastic Gradient Descent under a Strong Growth Condition

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-14T10:47:31.411341Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 77a35abd-4fcb-4c89-b5a7-2933697ae1f4 · outbound

This paper cites Global Convergence of Adaptive Gradient Methods for An Over-parameterized Neural Network.

Linear Convergence of Adaptive Stochastic Gradient Descent Global Convergence of Adaptive Gradient Methods for An Over-parameterized Neural Network

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-14T10:47:31.416037Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a0b0faa3-ae45-40ad-9c3b-1769a56a0136 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Linear Convergence of Adaptive Stochastic Gradient Descent Adam: A Method for Stochastic Optimization

Reference 2010

Resolution: unresolved; no resolver link, observed 2026-08-14T10:47:31.359712Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f4a679c-2d5e-4bbb-a109-ee8c53aa91ff · outbound

This paper cites Adaptive Bound Optimization for Online Convex Optimization.

Linear Convergence of Adaptive Stochastic Gradient Descent Adaptive Bound Optimization for Online Convex Optimization

Reference 2011

Resolution: unresolved; no resolver link, observed 2026-08-14T10:47:31.354327Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a279fb87-f15b-4112-b7d2-7bc0a0e96f4e · outbound

This paper cites Diagonal Rescaling For Neural Networks.

Linear Convergence of Adaptive Stochastic Gradient Descent Diagonal Rescaling For Neural Networks

Reference 2014

Resolution: verified exact; local_arxiv, observed 2026-08-14T10:47:31.631995Z

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.

Observation e54fa5fe-e7ce-4bf7-b501-f56eb3228447 · outbound

This paper cites A Convergence Theory for Deep Learning via Over-Parameterization.

Linear Convergence of Adaptive Stochastic Gradient Descent A Convergence Theory for Deep Learning via Over-Parameterization

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-14T10:47:31.343819Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9c02d46b-dbf4-4e69-9580-1d8f4f47814f · outbound

This paper cites On the Convergence of Adam and Beyond.

Linear Convergence of Adaptive Stochastic Gradient Descent On the Convergence of Adam and Beyond

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-14T10:47:31.370129Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2c219bbd-55e3-4a38-bbd7-6e3ab40b0eda · outbound

This paper cites Stochastic Gradient Descent Optimizes Over-parameterized Deep ReLU Networks.

Linear Convergence of Adaptive Stochastic Gradient Descent Stochastic Gradient Descent Optimizes Over-parameterized Deep ReLU Networks

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-14T10:47:31.349191Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e882a8e9-4bb5-4bd9-b6c9-6a8e06f19d78 · outbound

This paper cites On exponential convergence of SGD in non-convex over-parametrized learning.

Linear Convergence of Adaptive Stochastic Gradient Descent On exponential convergence of SGD in non-convex over-parametrized learning

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-14T10:47:31.406356Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.