Uniform Convergence of Deep Neural Networks With Lipschitz Continuous Activation Functions and Variable Widths

Yuesheng Xu, Haizhang Zhang

Open source

DOI: 10.1109/tit.2024.3439136
Published: 2024-10
Container: IEEE Transactions on Information Theory
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Open access: unknown

Credibility signals

uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

Show all credibility signals

supportingDOI registered: A matching record was returned by Crossref. Source: Crossref; license: CC0 metadata
supportingDOI resolves: A matching record was returned by Crossref. Source: Crossref; license: CC0 metadata
not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
supportingMetadata completeness: All 6 scored descriptive metadata groups are present. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer

Cite this work

BibTeX

@article{allodium:10.1109/tit.2024.3439136,
  title = {Uniform Convergence of Deep Neural Networks With Lipschitz Continuous Activation Functions and Variable Widths},
  author = {Yuesheng Xu and Haizhang Zhang},
  year = {2024},
  journal = {IEEE Transactions on Information Theory},
  doi = {10.1109/tit.2024.3439136},
  url = {https://doi.org/10.1109/tit.2024.3439136}
}

RIS

TY  - JOUR
TI  - Uniform Convergence of Deep Neural Networks With Lipschitz Continuous Activation Functions and Variable Widths
AU  - Yuesheng Xu
AU  - Haizhang Zhang
PY  - 2024
JO  - IEEE Transactions on Information Theory
DO  - 10.1109/tit.2024.3439136
UR  - https://doi.org/10.1109/tit.2024.3439136
ER  -

APA

Xu, Y., & Zhang, H. (2024). Uniform Convergence of Deep Neural Networks With Lipschitz Continuous Activation Functions and Variable Widths. IEEE Transactions on Information Theory. https://doi.org/10.1109/tit.2024.3439136

Source records

crossref · retrieved 2026-11-10T15:50:03.616Z