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Paper Citation Record · LEDGER

Hyper-Parameter Optimization: A Review of Algorithms and Applications

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2003.05689.

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

pith.paper-citation-record.v1
2003.05689 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T23:51:29.452388Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T00:57:30.248016Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

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 ef0b3a23-d5d1-4987-a631-1307f312f66d · inbound

A Robust Twin Parametric Margin Support Vector Machine for Multiclass Classification cites this paper.

A Robust Twin Parametric Margin Support Vector Machine for Multiclass Classification Hyper-Parameter Optimization: A Review of Algorithms and Applications

Reference 70

Resolution
verified exact
arxiv_id, observed 2026-05-24T08:26:04.206222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-24T08:25:50.438365Z digest=sha256:02ef2a18fa548827425ebef46f4d57fe492ae994a6502d936c4ad82a9b588c35

Observation 3ee70a7f-ac09-469f-a922-b480238f5b80 · inbound

Fine, I'll Merge It Myself: A Multi-Fidelity Framework for Automated Model Merging cites this paper.

Fine, I'll Merge It Myself: A Multi-Fidelity Framework for Automated Model Merging Hyper-Parameter Optimization: A Review of Algorithms and Applications

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-08T23:51:29.452388Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T23:51:29.452388Z digest=sha256:ce9c77ffacf11162c175017685b002917b565a49fada809fb2f353bb22ba14a5

Observation 7db41410-365e-4423-9409-fd51b4b66cf2 · inbound

Mock Deep Testing: Toward Separate Development of Data and Models for Deep Learning cites this paper.

Mock Deep Testing: Toward Separate Development of Data and Models for Deep Learning Hyper-Parameter Optimization: A Review of Algorithms and Applications

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-08T11:51:25.823829Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T11:51:25.823829Z digest=sha256:0ea4bca43864da8fb2dfd5cac2688d9bc63f75ee3106a18d9b43de20adcd31e2

Observation 4e4216c4-e61d-4165-aca3-c6d5e434994c · inbound

Unsupervised Machine Learning for Scientific Discovery: Workflow and Best Practices cites this paper.

Unsupervised Machine Learning for Scientific Discovery: Workflow and Best Practices Hyper-Parameter Optimization: A Review of Algorithms and Applications

Reference 191

Resolution
unresolved
no resolver link, observed 2026-08-07T10:45:05.087229Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:45:05.087229Z digest=sha256:265feb2df2835e20ccbf7c5f4f74a5fd037ee335ec283f80d2d2fd325b96fed3

Observation 62e02bc0-c114-440c-b48b-eb75a0891f7f · inbound

Hierarchical Deep Feature Fusion and Ensemble Learning for Enhanced Brain Tumor MRI Classification cites this paper.

Hierarchical Deep Feature Fusion and Ensemble Learning for Enhanced Brain Tumor MRI Classification Hyper-Parameter Optimization: A Review of Algorithms and Applications

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-07T00:55:35.051823Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:55:35.051823Z digest=sha256:bcf78b16cd5b7c1b21e08fe89a896d4aed3877e3fd5bd70b7930b3f77f8eb805

Observation b485e104-df5f-4ddb-9974-f5f1b54a1d3b · inbound

Fredholm Neural Networks for inverse problems in elliptic PDEs cites this paper.

Fredholm Neural Networks for inverse problems in elliptic PDEs Hyper-Parameter Optimization: A Review of Algorithms and Applications

Reference 77

Resolution
unresolved
no resolver link, observed 2026-08-06T19:22:33.045458Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:22:33.045458Z digest=sha256:50898bf310ff3b79690f3c386d519bb9f38e3b71552fd3ea025be47884f04f88

Observation 6af69aeb-ee97-4c61-a2fa-61f78a57c2cb · inbound

Hybrid Ensemble Approaches: Optimal Deep Feature Fusion and Hyperparameter-Tuned Classifier Ensembling for Enhanced Brain Tumor Classification cites this paper.

Hybrid Ensemble Approaches: Optimal Deep Feature Fusion and Hyperparameter-Tuned Classifier Ensembling for Enhanced Brain Tumor Classification Hyper-Parameter Optimization: A Review of Algorithms and Applications

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-06T16:55:34.589745Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:55:34.589745Z digest=sha256:f2856ddf9079c5874d60ccbe38db6b00c3315af1210301e877ac8a5ed1992972

Observation b1702588-0fdc-4176-a563-793878876f26 · inbound

Improving Neural Network Training using Dynamic Learning Rate Schedule for PINNs and Image Classification cites this paper.

Improving Neural Network Training using Dynamic Learning Rate Schedule for PINNs and Image Classification Hyper-Parameter Optimization: A Review of Algorithms and Applications

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-06T12:28:45.617655Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:28:45.617655Z digest=sha256:913dca2d1ef563c5d2bf260e32667ca53fb7496296779caf8b6e38bd99a16529

Observation c93bed6c-13c6-447c-bb01-345f0e31a0da · inbound

LATTEArena: An Evaluation Framework for LLM-powered Tabular Feature Engineering (Extended Version) cites this paper.

LATTEArena: An Evaluation Framework for LLM-powered Tabular Feature Engineering (Extended Version) Hyper-Parameter Optimization: A Review of Algorithms and Applications

Reference 49

Resolution
verified exact
arxiv_id, observed 2026-07-03T00:57:30.249634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-27T16:54:34.676936Z digest=sha256:60a126d093ea9f1b140fa0d4917894f21c417915b4ac9b9556a73f65cffd01b0

Observation 96a94ff7-54a9-40d0-b152-2092a3013955 · inbound

Exploiting Structural Properties for Efficient Constraint-Aware HNSW Hyperparameter Tuning cites this paper.

Exploiting Structural Properties for Efficient Constraint-Aware HNSW Hyperparameter Tuning Hyper-Parameter Optimization: A Review of Algorithms and Applications

Reference 48

Resolution
unresolved
no resolver link, observed 2026-07-11T16:08:01.254231Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T16:08:01.254231Z digest=sha256:a4b55d76165b98c8bb8f457adb47b795ef3ef054a6bdf77d70972ef1d970a338

Observation ad68417f-b65d-441e-b924-32d0cc08b105 · inbound

Efficient Heteroscedastic Bayesian Optimization for Risk-Aware AutoRL cites this paper.

Efficient Heteroscedastic Bayesian Optimization for Risk-Aware AutoRL Hyper-Parameter Optimization: A Review of Algorithms and Applications

Reference 8

Resolution
unresolved
no resolver link, observed 2026-07-31T00:13:47.132779Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T00:13:47.132779Z digest=sha256:35e231f7a97a3b2522e8a0e1bcd28e736c2229461af8c3f3a1ea6be9078f51f5

Observation 18b5331e-6ac2-466d-a1e6-a2398317bbeb · inbound

End-to-end differentiable retrieval of molecular spectra using hydrodynamics, chemistry, and radiative transfer cites this paper.

End-to-end differentiable retrieval of molecular spectra using hydrodynamics, chemistry, and radiative transfer Hyper-Parameter Optimization: A Review of Algorithms and Applications

Reference 217

Resolution
unresolved
no resolver link, observed 2026-08-03T00:39:23.156333Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T00:39:23.156333Z digest=sha256:e23d1dad8db4fd67cdc6f52bc3bc30c080047504d9f61bf7387f9b1aa4254de3