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Paper Citation Record · LEDGER

Generalized Convexity and Smoothness via Conjugate Duality: Optimization Theory for Deep Neural Networks

As of 16 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2608.09523.

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

pith.paper-citation-record.v1
2608.09523 v1

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T15:48:32.845600Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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

19 of 19 outbound references displayed

  • verified exact1
  • verified fuzzy1
  • unresolved13
  • parse uncertain0
  • malformed identifier3
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 55ef6603-1190-418f-bc0e-a1863bf8fd88 · outbound

This paper cites Improving Generalization Performance by Switching from Adam to SGD.

Generalized Convexity and Smoothness via Conjugate Duality: Optimization Theory for Deep Neural Networks Improving Generalization Performance by Switching from Adam to SGD

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-11T15:48:32.654669Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:48:32.654669Z digest=sha256:262118782aaa5a441537bfd3788cea1199c0ba095e027314d727c726e1e3aa1a

Observation b980bf8e-8e87-4e79-8040-e69c403b9ae6 · outbound

This paper cites an unresolved cited work.

Generalized Convexity and Smoothness via Conjugate Duality: Optimization Theory for Deep Neural Networks Unresolved cited work

Reference 12

Resolution
malformed identifier
no resolver link, observed 2026-08-11T15:48:32.660101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:48:32.660101Z digest=sha256:bfea85e9e25be5a3ecf07db9c12a365b363e40ac5c2bd8df8fb09e6a6a1bd609

Observation 83442916-15b2-455f-bcce-f8b5c7118d12 · outbound

This paper cites an unresolved cited work.

Generalized Convexity and Smoothness via Conjugate Duality: Optimization Theory for Deep Neural Networks Unresolved cited work

Reference 14

Resolution
unresolved
raw_fallback, observed 2026-08-11T15:48:33.573228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T15:48:32.773239Z digest=sha256:a05ad883c0afb94035d915453e708f0a679e403a2548da23afcf8f9be53c54c8

Observation f25e0a5c-681d-48af-a8bd-bf01ca13d2d5 · outbound

This paper cites Variance-reduced Clipping for Non-convex Optimization.

Generalized Convexity and Smoothness via Conjugate Duality: Optimization Theory for Deep Neural Networks Variance-reduced Clipping for Non-convex Optimization

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-11T15:48:32.823113Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:48:32.823113Z digest=sha256:72babaa1f38b6e24813796e7bf21d23f4573b17a6ac295b28c714ef3dd62aef8

Observation 3e49b2e7-192d-4699-b94a-a27f1a505e50 · outbound

This paper cites doi: 10.1016/ j.spa.2019.06.003.

Generalized Convexity and Smoothness via Conjugate Duality: Optimization Theory for Deep Neural Networks doi: 10.1016/ j.spa.2019.06.003

Reference 16

Resolution
malformed identifier
raw_fallback, observed 2026-08-11T15:48:33.505265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T15:48:32.828957Z digest=sha256:9469af3d1a1f1c81f903da3b1d68b0eb294d208285ad86696def2d468b6aeef1

Observation 29c4a038-1299-49dc-b733-5e2be9c8ecad · outbound

This paper cites an unresolved cited work.

Generalized Convexity and Smoothness via Conjugate Duality: Optimization Theory for Deep Neural Networks Unresolved cited work

Reference 18

Resolution
unresolved
raw_fallback, observed 2026-08-11T15:48:33.485281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T15:48:32.840251Z digest=sha256:7c5bc57323b7965fd999d947fbd68d205f253a0d7e4bf6116f68b07b209388ec

Observation 790f2062-5901-4103-b8cf-6586beccbbb2 · outbound

This paper cites an unresolved cited work.

Generalized Convexity and Smoothness via Conjugate Duality: Optimization Theory for Deep Neural Networks Unresolved cited work

Reference 1998

Resolution
malformed identifier
no resolver link, observed 2026-08-11T15:48:32.703931Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:48:32.703931Z digest=sha256:d1ee334356a3c7c02c92a5a3368f5539e2e9565995ffc15b23533a14a02693a9

Observation 33bfc3f2-fdd9-4e5c-b52a-86ccac27bc3d · outbound

This paper cites an unresolved cited work.

Generalized Convexity and Smoothness via Conjugate Duality: Optimization Theory for Deep Neural Networks Unresolved cited work

Reference 2001

Resolution
verified exact
doi, observed 2026-08-11T15:48:33.010241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T15:48:32.630732Z digest=sha256:df2a616a9045711c9cc9bdbc344d858c9638c2fc642e4a2a7521ac54064069b3

Observation 770bb704-93fd-420e-b245-3f8124281ded · outbound

This paper cites an unresolved cited work.

Generalized Convexity and Smoothness via Conjugate Duality: Optimization Theory for Deep Neural Networks Unresolved cited work

Reference 2006

Resolution
metadata mismatch
raw_fallback, observed 2026-08-11T15:48:33.437253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T15:48:32.619195Z digest=sha256:e9f2b5e708c5fe0a58c158cd2a2ce1e4e35a4f17a3d558e74af40e63722987ac

Observation 36959fd7-e598-4cde-b5bd-859dcafef6e9 · outbound

This paper cites Karhadkar, M.

Generalized Convexity and Smoothness via Conjugate Duality: Optimization Theory for Deep Neural Networks Karhadkar, M

Reference 2009

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:48:33.703629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T15:48:32.648996Z digest=sha256:1df05473a2f078a057f9c0fd4034a8906001d8cf7e290382a063fb483b1b5f9f

Observation 7f49b2bf-85f9-4c97-9f11-cff758e5eeb4 · outbound

This paper cites an unresolved cited work.

Generalized Convexity and Smoothness via Conjugate Duality: Optimization Theory for Deep Neural Networks Unresolved cited work

Reference 2013

Resolution
unresolved
no resolver link, observed 2026-08-11T15:48:32.834867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:48:32.834867Z digest=sha256:15dd26f1db00f09b3c93a8c69d11360b843f88a446d4bc9bb0104e697fc9e67d

Observation 559e1164-4864-4c63-9459-a250d62bf492 · outbound

This paper cites doi: 10.1017/CBO9780511804441.

Generalized Convexity and Smoothness via Conjugate Duality: Optimization Theory for Deep Neural Networks doi: 10.1017/CBO9780511804441

Reference 2014

Resolution
unresolved
no resolver link, observed 2026-08-11T15:48:32.606271Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:48:32.606271Z digest=sha256:ffaff2715ba4e4a79d86104a89276074da8ad6dfa4f0d7a8639657b2f2ad3435

Observation 8e357238-7846-409e-a224-9831895e48b5 · outbound

This paper cites doi: 10.1109/CVPR.2016.90.

Generalized Convexity and Smoothness via Conjugate Duality: Optimization Theory for Deep Neural Networks doi: 10.1109/CVPR.2016.90

Reference 2016

Resolution
unresolved
no resolver link, observed 2026-08-11T15:48:32.636372Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:48:32.636372Z digest=sha256:d2e1fd558a33bde09cb3b2d2883896144a774838b667762c936a0c6700a38f70

Observation 5e095a8a-431b-4e70-835b-229f48c2a27f · outbound

This paper cites an unresolved cited work.

Generalized Convexity and Smoothness via Conjugate Duality: Optimization Theory for Deep Neural Networks Unresolved cited work

Reference 2018

Resolution
unresolved
no resolver link, observed 2026-08-11T15:48:32.599567Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:48:32.599567Z digest=sha256:4658fc87b6d84ebfb9ee43d4acbfe3dcc40fecbfd34b4d6e239db897e2b4ffd7

Observation fd039348-3051-4517-acf1-cec68b5688de · outbound

This paper cites Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms.

Generalized Convexity and Smoothness via Conjugate Duality: Optimization Theory for Deep Neural Networks Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-11T15:48:32.845600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:48:32.845600Z digest=sha256:4c31e98d008cec63d1af63474f344f425d5bf9c3fcb3c18ab0f3a258c0f169da

Observation 732b2156-7642-44c8-a993-18ea2b5824df · outbound

This paper cites an unresolved cited work.

Generalized Convexity and Smoothness via Conjugate Duality: Optimization Theory for Deep Neural Networks Unresolved cited work

Reference 2020

Resolution
unresolved
no resolver link, observed 2026-08-11T15:48:32.612360Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:48:32.612360Z digest=sha256:2789d1a50a18323715fe1773bdc9ec0ce68a7596ec4dfe83f11e8eaa2ce5745d

Observation 5cff68d9-c0e2-4a64-9274-a725b8814734 · outbound

This paper cites an unresolved cited work.

Generalized Convexity and Smoothness via Conjugate Duality: Optimization Theory for Deep Neural Networks Unresolved cited work

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-11T15:48:32.643115Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:48:32.643115Z digest=sha256:f53443fa3df662bcc44ee0dc43a050e84490e07525e405349b57135ee50831b3

Observation cbe936c5-d953-495e-9f6e-3b6d020b04eb · outbound

This paper cites an unresolved cited work.

Generalized Convexity and Smoothness via Conjugate Duality: Optimization Theory for Deep Neural Networks Unresolved cited work

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-11T15:48:32.495365Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:48:32.495365Z digest=sha256:889de3f0c8f5d9c2da2b96b5297f2af8d628539f0aa6a1c62cafd704dc45eccf

Observation 8bfcd308-f545-4589-b676-9e7bbfd01329 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Generalized Convexity and Smoothness via Conjugate Duality: Optimization Theory for Deep Neural Networks An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-11T15:48:32.624798Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:48:32.624798Z digest=sha256:b93891b095901a5ba0d8ff08a4f130be880529ae00cb6137680babd0e62461ad

Pith citing papers

No inbound Pith citation observations are available.