Paper Citation Record · LEDGER

One-Step Early Stopping Strategy using Neural Tangent Kernel Theory and Rademacher Complexity

As of 21 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 0 inbound Pith citation observations for arXiv:2411.18806.

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

pith.paper-citation-record.v1
2411.18806 v1

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T10:59:06.323609Z

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+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

13 of 13 outbound references displayed

verified exact0
verified fuzzy8
unresolved5
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8a78f6db-4570-49ac-a781-c96cd36adf9a · outbound

This paper cites Neural networks for fast optimisation in model predictive control: A review,.

One-Step Early Stopping Strategy using Neural Tangent Kernel Theory and Rademacher Complexity Neural networks for fast optimisation in model predictive control: A review,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-12T10:59:06.278250Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 51257fbe-815e-41aa-ac83-25a7ac7ceacb · outbound

This paper cites Neural tangent kernel: Con- vergence and generalization in neural networks,.

One-Step Early Stopping Strategy using Neural Tangent Kernel Theory and Rademacher Complexity Neural tangent kernel: Con- vergence and generalization in neural networks,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:59:06.570167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 045d7450-91da-4319-9230-16ef152d0aab · outbound

This paper cites Gradient Descent Provably Optimizes Over-parameterized Neural Networks.

One-Step Early Stopping Strategy using Neural Tangent Kernel Theory and Rademacher Complexity Gradient Descent Provably Optimizes Over-parameterized Neural Networks

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-12T10:59:06.285824Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 22a75806-2444-4d6d-a73e-8a7a923010bc · outbound

This paper cites Fine-grained analysis of optimization and generalization for overparameterized two-layer neural networks,.

One-Step Early Stopping Strategy using Neural Tangent Kernel Theory and Rademacher Complexity Fine-grained analysis of optimization and generalization for overparameterized two-layer neural networks,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:59:06.559030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 29c7a8a9-567e-4268-94d4-be87dc588daf · outbound

This paper cites Generalization Guarantees for Neural Networks via Harnessing the Low-rank Structure of the Jacobian.

One-Step Early Stopping Strategy using Neural Tangent Kernel Theory and Rademacher Complexity Generalization Guarantees for Neural Networks via Harnessing the Low-rank Structure of the Jacobian

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-12T10:59:06.293828Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f99084aa-da01-478f-8300-230a6f6673b2 · outbound

This paper cites Implicit bias of MSE gradient optimiza- tion in underparameterized neural networks,.

One-Step Early Stopping Strategy using Neural Tangent Kernel Theory and Rademacher Complexity Implicit bias of MSE gradient optimiza- tion in underparameterized neural networks,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:59:06.547034Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 47eca9f0-4a84-46b6-a1f7-1a193a85a2e5 · outbound

This paper cites Training and generalization errors for underparameterized neural networks,.

One-Step Early Stopping Strategy using Neural Tangent Kernel Theory and Rademacher Complexity Training and generalization errors for underparameterized neural networks,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:59:06.534202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6399e108-210d-44fa-9e1b-9d9f99bb456b · outbound

This paper cites Founda- tions of machine learning,.

One-Step Early Stopping Strategy using Neural Tangent Kernel Theory and Rademacher Complexity Founda- tions of machine learning,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:59:06.522940Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c2460a4e-8712-4c19-9076-ad618b0232a7 · outbound

This paper cites Rademacher and gaussian complex- ities: Risk bounds and structural results,.

One-Step Early Stopping Strategy using Neural Tangent Kernel Theory and Rademacher Complexity Rademacher and gaussian complex- ities: Risk bounds and structural results,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:59:06.511526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation bc194fbc-5818-4e36-87c4-bfd3c2857809 · outbound

This paper cites Lecture notes for machine learning theory,.

One-Step Early Stopping Strategy using Neural Tangent Kernel Theory and Rademacher Complexity Lecture notes for machine learning theory,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:59:06.500792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ce65bcd8-f8d6-47f5-b618-a04f1667a2d3 · outbound

This paper cites Benign overfitting in linear regression,.

One-Step Early Stopping Strategy using Neural Tangent Kernel Theory and Rademacher Complexity Benign overfitting in linear regression,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-12T10:59:06.316002Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 73ac8217-890f-49fb-9e7d-a71cbadaa5a5 · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library,.

One-Step Early Stopping Strategy using Neural Tangent Kernel Theory and Rademacher Complexity Pytorch: An imperative style, high-performance deep learning library,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:59:06.487581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ad96ca48-d96a-4232-a518-ba69cc18d519 · outbound

This paper cites On the Rademacher Complexity of Linear Hypothesis Sets.

One-Step Early Stopping Strategy using Neural Tangent Kernel Theory and Rademacher Complexity On the Rademacher Complexity of Linear Hypothesis Sets

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-12T10:59:06.323609Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.