Paper Citation Record · LEDGER

Provable Complexity Improvement of AdaGrad over SGD: Upper and Lower Bounds in Stochastic Non-Convex Optimization

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2406.04592.

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

pith.paper-citation-record.v1
2406.04592 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:54:33.814364Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-13T20:58:15.734279Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
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malformed identifier0
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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 6c5c583a-ea5e-4296-b05e-04138342fc7f · inbound

Fast Stochastic Second-Order Adagrad for Nonconvex Bound-Constrained Optimization cites this paper.

Fast Stochastic Second-Order Adagrad for Nonconvex Bound-Constrained Optimization Provable Complexity Improvement of AdaGrad over SGD: Upper and Lower Bounds in Stochastic Non-Convex Optimization

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-15T22:54:33.814364Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d7452adf-7dba-458a-a72c-1b33a7ef44c3 · inbound

SGD with Adaptive Preconditioning: Unified Analysis and Momentum Acceleration cites this paper.

SGD with Adaptive Preconditioning: Unified Analysis and Momentum Acceleration Provable Complexity Improvement of AdaGrad over SGD: Upper and Lower Bounds in Stochastic Non-Convex Optimization

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T21:45:07.761309Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb405e5a-dfea-42ed-b37a-658bd3181d3d · inbound

Non-Euclidean SGD for Structured Optimization: Unified Analysis and Improved Rates cites this paper.

Non-Euclidean SGD for Structured Optimization: Unified Analysis and Improved Rates Provable Complexity Improvement of AdaGrad over SGD: Upper and Lower Bounds in Stochastic Non-Convex Optimization

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-03T22:20:05.547507Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1fbab019-480c-4942-9966-a31379e52df6 · inbound

Optimal Projection-Free Adaptive SGD for Matrix Optimization cites this paper.

Optimal Projection-Free Adaptive SGD for Matrix Optimization Provable Complexity Improvement of AdaGrad over SGD: Upper and Lower Bounds in Stochastic Non-Convex Optimization

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-13T20:58:15.735847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 143d654f-2f15-4a05-99a1-b8169616974c · inbound

A unified convergence theory for adaptive first-order methods in the nonconvex case, including AdaNorm, full and diagonal AdaGrad, Shampoo and Muo cites this paper.

A unified convergence theory for adaptive first-order methods in the nonconvex case, including AdaNorm, full and diagonal AdaGrad, Shampoo and Muo Provable Complexity Improvement of AdaGrad over SGD: Upper and Lower Bounds in Stochastic Non-Convex Optimization

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-10T07:26:59.838893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7ee54a71-d2e5-47f8-929b-96ac55cfdafa · inbound

Optimizer-Model Consistency: Full Finetuning with the Same Optimizer as Pretraining Forgets Less cites this paper.

Optimizer-Model Consistency: Full Finetuning with the Same Optimizer as Pretraining Forgets Less Provable Complexity Improvement of AdaGrad over SGD: Upper and Lower Bounds in Stochastic Non-Convex Optimization

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-11T19:26:08.606390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.