Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-05T18:25:28.334734Z
Paper Citation Record · LEDGER
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning
As of 8 August 2026, this Paper Citation Record lists 56 of 56 outbound references and 0 inbound Pith citation observations for arXiv:2608.03482.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
56 of 56 outbound references displayed
- verified exact1
- verified fuzzy43
- unresolved10
- parse uncertain0
- malformed identifier2
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 6555c0b7-e725-476e-a751-24e220459b89 · outbound
This paper cites Survey on svm and their application in image classification.International Journal of Information Technology, 13(5):1–11, 2021.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning Survey on svm and their application in image classification.International Journal of Information Technology, 13(5):1–11, 2021
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T18:25:37.399372Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation d5f87452-6646-4428-a8d6-80446c5e2cf6 · outbound
This paper cites Applicationsofsupportvectormachine(svm)learningincancergenomics.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning Applicationsofsupportvectormachine(svm)learningincancergenomics
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T18:25:37.123403Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation edff40a4-db7d-4615-9857-b845c4f1d193 · outbound
This paper cites an unresolved cited work.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning Unresolved cited work
Reference 3
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T18:25:36.894329Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 9235367d-9faf-493d-9ae8-5af73982a05a · outbound
This paper cites A review of optimization methodologies in support vector machines.Neurocomputing, 74(17):3609–3618, 2011.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning A review of optimization methodologies in support vector machines.Neurocomputing, 74(17):3609–3618, 2011
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T18:25:36.656254Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 9363f35e-a7a7-4c9b-8c83-a2b75718ffcc · outbound
This paper cites A novel active learning method using svm for text classification.International Journal of Au- tomation and Computing, 15(3):290–298, 2018.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning A novel active learning method using svm for text classification.International Journal of Au- tomation and Computing, 15(3):290–298, 2018
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T18:25:36.417537Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 2de1aefc-22ed-49de-86e6-774c152ecca9 · outbound
This paper cites Face recognition by support vector machines.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning Face recognition by support vector machines
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T18:25:36.140894Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 9453548b-2604-4e5e-af08-e825cace3b8d · outbound
This paper cites Biological applications of support vector machines.Briefings in bioin- formatics, 5(4):328–338, 2004.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning Biological applications of support vector machines.Briefings in bioin- formatics, 5(4):328–338, 2004
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T18:25:35.894354Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation f080bde2-5c3f-44a5-b87a-e4acee1cfef6 · outbound
This paper cites Quantum support vector machine for classification task: A review.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning Quantum support vector machine for classification task: A review
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T18:25:35.585202Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 4d9095e8-25b2-4811-96f3-612ea791a5dc · outbound
This paper cites The complexity of quantum support vector machines.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning The complexity of quantum support vector machines
Reference 9
- Resolution
- malformed identifier
- no resolver link, observed 2026-08-05T18:25:24.418725Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 295efad1-1dc5-44b2-b965-8ba0808721f4 · outbound
This paper cites Performance analysis of classical and quantum support vector machines for diagnosis of chronic kidney disease.Informatics and Health, 2025.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning Performance analysis of classical and quantum support vector machines for diagnosis of chronic kidney disease.Informatics and Health, 2025
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T18:25:35.377671Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation cf41463d-4a89-4730-9fe5-ba246c8e65d1 · outbound
This paper cites Practical application improvement to Quantum SVM: theory to practice.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning Practical application improvement to Quantum SVM: theory to practice
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T18:25:24.547490Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 455ccd14-7a48-42ac-a3b1-eaa64bfeacd8 · outbound
This paper cites Ensemble and optimization algorithm in support vector machines for classification of wheat genotypes.Scientific Reports, 14(1):22728, 2024.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning Ensemble and optimization algorithm in support vector machines for classification of wheat genotypes.Scientific Reports, 14(1):22728, 2024
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T18:25:35.130817Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 3323c426-8d6e-43a2-9bae-cd1c119f61d3 · outbound
This paper cites Radial basis function kernel optimization for Support Vector Machine classifiers.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning Radial basis function kernel optimization for Support Vector Machine classifiers
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T18:25:24.685754Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 18ccfa6a-0f1c-450b-8c0f-2b666bb2a7ef · outbound
This paper cites Support vector machines and kernels for computational biology.PLoS computa- tional biology, 4(10):e1000173, 2008.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning Support vector machines and kernels for computational biology.PLoS computa- tional biology, 4(10):e1000173, 2008
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T18:25:34.762730Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation c2d766f6-f785-4272-bee1-e1547882a714 · outbound
This paper cites Exploring kernel machines and support vector machines: Principles, techniques, and future directions.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning Exploring kernel machines and support vector machines: Principles, techniques, and future directions
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T18:25:34.508464Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation af3d24d3-c104-408e-9acc-0bc9cdaff102 · outbound
This paper cites Model selection for support vector machines.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning Model selection for support vector machines
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T18:25:34.334274Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation a8f2db42-1038-4116-8446-9657ec689fa2 · outbound
This paper cites An overview on the advancements of support vector machine models in healthcare applications: a review.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning An overview on the advancements of support vector machine models in healthcare applications: a review
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T18:25:34.141475Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 995866d8-3d50-4d11-b436-0ad3b2b1d448 · outbound
This paper cites An Orthogonal Polynomial Kernel-Based Machine Learning Model for Differential-Algebraic Equations.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning An Orthogonal Polynomial Kernel-Based Machine Learning Model for Differential-Algebraic Equations
Reference 18
- Resolution
- verified exact
- local_arxiv, observed 2026-08-05T18:25:28.811438Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 7aa3596d-9870-49d9-b9fa-3eec56216988 · outbound
This paper cites Rational jacobi kernel functions: A novel massively parallelizable orthogonal kernel for support vector machines.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning Rational jacobi kernel functions: A novel massively parallelizable orthogonal kernel for support vector machines
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T18:25:33.920124Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 1df9af86-f213-4474-8abe-ea80df3671a8 · outbound
This paper cites New hermite orthogonal poly- nomial kernel and combined kernels in support vector machine classifier.Pattern Recog- nition, 60:921–935, 2016.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning New hermite orthogonal poly- nomial kernel and combined kernels in support vector machine classifier.Pattern Recog- nition, 60:921–935, 2016
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T18:25:33.742801Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 88dbc70f-99df-4809-bc96-697bcf15790e · outbound
This paper cites A novel formulation of orthogonal polynomial kernel functions for svm classifiers: The gegenbauer family.Pattern Recognition, 84:211–225, 2018.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning A novel formulation of orthogonal polynomial kernel functions for svm classifiers: The gegenbauer family.Pattern Recognition, 84:211–225, 2018
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T18:25:33.557058Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation baa84e93-743f-4d66-ad94-a2bce3aea137 · outbound
This paper cites A review of q-difference equations for al-salam–carlitz polynomials and applications to u (n+ 1) type generating functions and ramanujan’s integrals.Mathematics, 11(7):1655, 2023.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning A review of q-difference equations for al-salam–carlitz polynomials and applications to u (n+ 1) type generating functions and ramanujan’s integrals.Mathematics, 11(7):1655, 2023
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T18:25:33.384766Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation e97250e4-2b24-4515-8c58-018c738a9390 · outbound
This paper cites Hypergeometric orthogonal polynomials.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning Hypergeometric orthogonal polynomials
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T18:25:33.159858Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation dd19f301-6b85-43a8-b6de-fa0508505503 · outbound
This paper cites Bivariate continuous q-hermite poly- nomials and deformed quantum serre relations.Journal of Algebra and Its Applications, 20(01):2140016, 2021.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning Bivariate continuous q-hermite poly- nomials and deformed quantum serre relations.Journal of Algebra and Its Applications, 20(01):2140016, 2021
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T18:25:33.066181Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 840ac44b-e872-4b21-b843-9cd827ff9595 · outbound
This paper cites Deformed gaussian operators on weighted q-fock spaces.Journal of Stochastic Analysis, 1(4):6, 2020.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning Deformed gaussian operators on weighted q-fock spaces.Journal of Stochastic Analysis, 1(4):6, 2020
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T18:25:32.944827Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 93605e43-2747-498f-9a83-2f18a553ba5f · outbound
This paper cites Supportvectormachinewithorthogonal chebyshev kernel.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning Supportvectormachinewithorthogonal chebyshev kernel
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T18:25:32.816466Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation e7303c9d-cbec-43f8-bc15-51604fb178a1 · outbound
This paper cites A set of new chebyshev kernel functions for support vector machine pattern classification.Pattern Recognition, 44(7):1435–1447, 2011.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning A set of new chebyshev kernel functions for support vector machine pattern classification.Pattern Recognition, 44(7):1435–1447, 2011
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T18:25:32.623170Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation ca250d7b-8931-4add-950f-7648dfe08269 · outbound
This paper cites An adaptive support vector regression based on a new sequence of unified orthogonal polynomials.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning An adaptive support vector regression based on a new sequence of unified orthogonal polynomials
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T18:25:32.494744Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 8054515e-9b7a-49e9-9ad9-5aae1dd1ecfd · outbound
This paper cites Some sets of orthogonal polynomial kernel functions.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning Some sets of orthogonal polynomial kernel functions
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T18:25:32.323064Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 1c601e3e-7721-47d7-951a-c2cce6849e26 · outbound
This paper cites Number 2.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning Number 2
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T18:25:32.140796Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 205b946a-7579-4d10-a160-16b468976243 · outbound
This paper cites Springer Science & Business Media, 2012.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning Springer Science & Business Media, 2012
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T18:25:32.005848Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 1284ee85-4c7d-49a6-8015-683e179fdc84 · outbound
This paper cites Cambridge university press, 2011.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning Cambridge university press, 2011
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T18:25:31.849956Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 24c258ba-5e0f-4054-bae2-aaaabc273ab9 · outbound
This paper cites Springer Science & Business Media, 2012.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning Springer Science & Business Media, 2012
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T18:25:31.712507Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 50efc990-fda4-40d8-b8b1-ccb54546ec39 · outbound
This paper cites Onsecond order q-difference equations satisfied by al-salam–carlitz i-sobolev type polynomials of higher order.Mathematics, 8(8):1300, 2020.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning Onsecond order q-difference equations satisfied by al-salam–carlitz i-sobolev type polynomials of higher order.Mathematics, 8(8):1300, 2020
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T18:25:31.578125Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 31d2b312-bdcf-464f-9060-63d879493cd1 · outbound
This paper cites On combinatorics of al-salam carlitz polynomials.European Journal of Combinatorics, 18(3):295–302, 1997.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning On combinatorics of al-salam carlitz polynomials.European Journal of Combinatorics, 18(3):295–302, 1997
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T18:25:31.490004Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation d59f37f3-45a8-441c-82e0-5a5927db8cbc · outbound
This paper cites Multivariable al–salam & carlitz polynomials associated with the type a q–dunkl kernel.Mathematische Nachrichten, 212(1):5–35, 2000.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning Multivariable al–salam & carlitz polynomials associated with the type a q–dunkl kernel.Mathematische Nachrichten, 212(1):5–35, 2000
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T18:25:31.336308Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation f42f9649-717c-4d84-a246-d7e16eb6cce6 · outbound
This paper cites On discrete orthogonal polynomials of several variables.Advances in Applied Mathematics, 33(3):615–632, 2004.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning On discrete orthogonal polynomials of several variables.Advances in Applied Mathematics, 33(3):615–632, 2004
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T18:25:31.208013Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 30806156-28ff-4f35-aad3-937167dacb1f · outbound
This paper cites Constructing support vector machine kernels from orthogonal polynomials for face and speaker verification.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning Constructing support vector machine kernels from orthogonal polynomials for face and speaker verification
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T18:25:31.098570Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation f4226bda-4617-4803-a732-f8251c8187fd · outbound
This paper cites Bohb: Robust and efficient hyperpa- rameter optimization at scale.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning Bohb: Robust and efficient hyperpa- rameter optimization at scale
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T18:25:30.996134Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 9c061bb9-7a0c-407f-b2c4-c7dfb1220921 · outbound
This paper cites OptunaHub: A Platform for Black-Box Optimization.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning OptunaHub: A Platform for Black-Box Optimization
Reference 40
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T18:25:26.958539Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bd3e5253-2754-436f-b0d0-235967235695 · outbound
This paper cites Algorithms for hyper- parameter optimization.Advances in neural information processing systems, 24, 2011.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning Algorithms for hyper- parameter optimization.Advances in neural information processing systems, 24, 2011
Reference 41
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T18:25:27.021313Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 40dbeb3d-3ca7-4fb4-aff2-32a7796dbd8b · outbound
This paper cites Hyperparameter optimization.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning Hyperparameter optimization
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T18:25:30.885699Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 5e95b7fa-6e0f-4850-a4d2-fded5e848d78 · outbound
This paper cites The entire regularization path for the support vector machine.Journal of Machine Learning Research, 5(Oct):1391– 1415, 2004.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning The entire regularization path for the support vector machine.Journal of Machine Learning Research, 5(Oct):1391– 1415, 2004
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T18:25:30.686806Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 55b53883-6708-48c8-a94d-0f738501d465 · outbound
This paper cites an unresolved cited work.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning Unresolved cited work
Reference 44
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T18:25:30.548081Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 226772df-161d-4b97-a31b-d0111bcb8ddd · outbound
This paper cites Efficient kernel selection via spectral analysis.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning Efficient kernel selection via spectral analysis
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T18:25:30.407054Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 4e1047ec-e5e0-4297-8013-53daecb85527 · outbound
This paper cites Infinite kernel learning: generalization bounds and algorithms.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning Infinite kernel learning: generalization bounds and algorithms
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T18:25:30.190538Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 4915dcd8-99ec-498f-b160-febf77abe56e · outbound
This paper cites an unresolved cited work.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning Unresolved cited work
Reference 47
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T18:25:30.038860Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation d8e2fece-ab5a-45b5-bc5c-f11ec57fd792 · outbound
This paper cites Performance evaluation in machine learning: the good, the bad, the ugly, and the way forward.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning Performance evaluation in machine learning: the good, the bad, the ugly, and the way forward
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T18:25:29.841850Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 999406b1-c1c1-46b7-b783-db0e4c9001e8 · outbound
This paper cites Statistical comparisons of classifiers over multiple data sets.Journal of Machine learning research, 7(Jan):1–30, 2006.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning Statistical comparisons of classifiers over multiple data sets.Journal of Machine learning research, 7(Jan):1–30, 2006
Reference 49
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T18:25:27.651777Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 02baa739-d2d1-42e4-9558-56849efa1904 · outbound
This paper cites an unresolved cited work.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning Unresolved cited work
Reference 50
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T18:25:29.692460Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 6c5be207-e681-46da-bae7-2e00c5666def · outbound
This paper cites Time for a change: a tutorial for comparing multiple classifiers through bayesian analysis.Journal of Machine Learning Research, 18(77):1–36, 2017.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning Time for a change: a tutorial for comparing multiple classifiers through bayesian analysis.Journal of Machine Learning Research, 18(77):1–36, 2017
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T18:25:29.577082Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 17edc303-9c25-4837-8995-08c602a6c28a · outbound
This paper cites Accounting for variance in machine learning benchmarks.Proceedings of Machine Learning and Systems, 3:747–769, 2021.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning Accounting for variance in machine learning benchmarks.Proceedings of Machine Learning and Systems, 3:747–769, 2021
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T18:25:29.362812Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 1cefcf9b-a24c-455e-977e-d1d6762f0b0d · outbound
This paper cites The asa statement on p-values: context, process, and purpose, 2016.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning The asa statement on p-values: context, process, and purpose, 2016
Reference 53
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T18:25:27.992842Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 589af494-8d70-4f77-b7d0-b721ca298428 · outbound
This paper cites Dataset meta-level and statistical features affect machine learning performance.Scientific Reports, 14(1):1670, 2024.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning Dataset meta-level and statistical features affect machine learning performance.Scientific Reports, 14(1):1670, 2024
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T18:25:29.217117Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation dd33bb07-0dd6-43f9-83d0-4c8401b55f08 · outbound
This paper cites Impact of dataset size on classi- fication performance: an empirical evaluation in the medical domain.Applied sciences, 11(2):796, 2021.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning Impact of dataset size on classi- fication performance: an empirical evaluation in the medical domain.Applied sciences, 11(2):796, 2021
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T18:25:28.999874Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 562fc417-04da-41bc-8afb-244f226ce2dd · outbound
This paper cites Avoiding common machine learning pitfalls.Patterns, 5(10), 2024.
Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning Avoiding common machine learning pitfalls.Patterns, 5(10), 2024
Reference 56
- Resolution
- malformed identifier
- raw_fallback, observed 2026-08-05T18:25:28.651522Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Pith citing papers
No inbound Pith citation observations are available.