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Paper Citation Record · LEDGER

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain

As of 9 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2606.08212.

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

pith.paper-citation-record.v1
2606.08212 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-27T20:13:54.929965Z

measured 42 of 42 standing notices

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

measured 0 of 0 inbound itemization

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measured 0 of 1 external citation measurements

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

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Reference resolution

42 of 42 outbound references displayed

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  • unresolved38
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Outbound references

Observation 2b17c74a-6a71-4788-8f8b-15136e9cefd4 · outbound

This paper cites D-smartml: A distributed automated machine learning framework.

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain D-smartml: A distributed automated machine learning framework

Reference 1

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Observation 931f6c84-a57f-490a-ae39-54dd141f5f30 · outbound

This paper cites A new look at the statistical model identification.IEEE transactions on automatic control, 19(6):716–723, 1974.

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain A new look at the statistical model identification.IEEE transactions on automatic control, 19(6):716–723, 1974

Reference 2

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Observation f75331fd-085e-432f-910f-9ab6f9a8ca56 · outbound

This paper cites A roadmap of clustering algorithms: finding a match for a biomedical application.Briefings in Bioinfor- matics, 10(3):297–314, 2009.

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain A roadmap of clustering algorithms: finding a match for a biomedical application.Briefings in Bioinfor- matics, 10(3):297–314, 2009

Reference 4

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Observation e38cb22b-dc4c-4810-9359-dc5197ecd872 · outbound

This paper cites A survey on machine-learning techniques in cognitive radios.IEEE Communications Surveys & Tutorials, 15(3):1136– 1159, 2012.

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain A survey on machine-learning techniques in cognitive radios.IEEE Communications Surveys & Tutorials, 15(3):1136– 1159, 2012

Reference 5

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Observation d33ff1ad-7f58-4c35-b768-57d2c4fccbca · outbound

This paper cites Au- tostacker: A compositional evolutionary learning system.

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain Au- tostacker: A compositional evolutionary learning system

Reference 6

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Observation 2eb3aaeb-9ff3-45d9-875b-50cd806de0de · outbound

This paper cites Au- tostacker: A compositional evolutionary learning system.

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain Au- tostacker: A compositional evolutionary learning system

Reference 7

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Observation e7a9b8c0-3cf2-449a-9ef9-b7337db81e04 · outbound

This paper cites A survey on machine learning: concept, algo- rithms and applications.International Journal of Innovative Research in Computer and Communication Engineering, 5(2):1301–1309, 2017.

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain A survey on machine learning: concept, algo- rithms and applications.International Journal of Innovative Research in Computer and Communication Engineering, 5(2):1301–1309, 2017

Reference 8

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source=pdf_text observed=2026-06-27T20:13:54.929965Z digest=sha256:3a40e11b8f262f98737ca7e1b0c3033b2247a0f7721f15987123863723008cea

Observation 56b49856-0cb4-4c45-9916-d5219b60c742 · outbound

This paper cites A comparison of multiple classification methods for diagnosis of parkinson disease.Expert Systems with Applications, 37(2):1568–1572, 2010.

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain A comparison of multiple classification methods for diagnosis of parkinson disease.Expert Systems with Applications, 37(2):1568–1572, 2010

Reference 9

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Observation 7b067720-3c94-4801-8354-7c69f7eb4af5 · outbound

This paper cites Recipe: a grammar-based framework for automatically evolving classification pipelines.

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain Recipe: a grammar-based framework for automatically evolving classification pipelines

Reference 10

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Observation 39b9c2c3-cb3d-4a7b-bce5-a23144f861ee · outbound

This paper cites AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data.

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data

Reference 12

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Observation 49f2cdf1-d782-4256-b48b-3284b8f6cabd · outbound

This paper cites Survey of machine learning algorithms for disease diagnostic.Journal of Intelligent Learning Systems and Applications, 9(01):1, 2017.

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain Survey of machine learning algorithms for disease diagnostic.Journal of Intelligent Learning Systems and Applications, 9(01):1, 2017

Reference 14

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Observation a0687945-3223-4fbd-b940-3084bed70ec3 · outbound

This paper cites Multi-interval discretization of continuous-valued attributes for classification learning.

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain Multi-interval discretization of continuous-valued attributes for classification learning

Reference 15

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Observation 00c93e6b-df97-4026-af32-5c6a8c12d432 · outbound

This paper cites Practical automated machine learning for the automl challenge 2018.

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain Practical automated machine learning for the automl challenge 2018

Reference 16

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Observation 7a1f8e19-338a-40ad-b671-bc5a01d45a0d · outbound

This paper cites Practical automated machine learning for the automl challenge 2018.

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain Practical automated machine learning for the automl challenge 2018

Reference 17

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Observation ff215529-528f-4842-ad1d-2ee167027c89 · outbound

This paper cites Auto-sklearn: efficient and robust automated machine learning.

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain Auto-sklearn: efficient and robust automated machine learning

Reference 18

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Observation 55e7f717-9cf5-4bd4-93cb-02dace45a2ce · outbound

This paper cites P4ml: A phased performance-based pipeline planner for automated machine learning.

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain P4ml: A phased performance-based pipeline planner for automated machine learning

Reference 19

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Observation 58f1c64c-f6d2-461e-abb6-272fbb176077 · outbound

This paper cites Pspso: A package for parameters selection using particle swarm optimization.SoftwareX, 15:100706, 2021.

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain Pspso: A package for parameters selection using particle swarm optimization.SoftwareX, 15:100706, 2021

Reference 20

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Observation d4d29668-fb8e-42fd-8892-15facaca1351 · outbound

This paper cites The determination of the order of an autoregression.

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain The determination of the order of an autoregression

Reference 21

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Observation 522b93f3-e7c9-4a01-858f-7adc036f5a1a · outbound

This paper cites Supervised machine learning: A re- view of classification techniques.Emerging artificial intelligence applications in computer engineering, 160(1):3–24, 2007.

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain Supervised machine learning: A re- view of classification techniques.Emerging artificial intelligence applications in computer engineering, 160(1):3–24, 2007

Reference 22

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Observation 67b162d1-009c-4a32-b78d-274add58abba · outbound

This paper cites Auto-WEKA: Automatic model selection and hyperparameter optimization in WEKA, pages 81–95.

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain Auto-WEKA: Automatic model selection and hyperparameter optimization in WEKA, pages 81–95

Reference 23

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Observation af503426-8598-495f-9d23-8aac985dd196 · outbound

This paper cites H2o automl: Scalable automatic machine learning.

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain H2o automl: Scalable automatic machine learning

Reference 24

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Observation 5a1d4fcb-7003-4143-ac05-341b94d7b34a · outbound

This paper cites Smartml: A meta learning-based framework for auto- mated selection and hyperparameter tuning for machine learning algorithms.

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain Smartml: A meta learning-based framework for auto- mated selection and hyperparameter tuning for machine learning algorithms

Reference 25

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Observation cbc97296-0582-4438-bce2-7e72af96db0d · outbound

This paper cites Metwalli.

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain Metwalli

Reference 26

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Observation 035febc2-6b56-4180-9703-954c9d4d9a12 · outbound

This paper cites an unresolved cited work.

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain Unresolved cited work

Reference 27

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Observation 8800550f-9a6e-44bc-b07d-467719ff0f9f · outbound

This paper cites Machine learning algorithm cheat sheet for azure machine learning designer.

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain Machine learning algorithm cheat sheet for azure machine learning designer

Reference 28

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Observation 155b6cae-296f-4544-b28f-54892c38549c · outbound

This paper cites Ml-plan: Automated machine learning via hierarchical planning.Machine Learning, 107(8):1495–1515, 2018.

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain Ml-plan: Automated machine learning via hierarchical planning.Machine Learning, 107(8):1495–1515, 2018

Reference 29

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Observation d7cdcc28-17ee-4f5b-a94c-361bcea57dd5 · outbound

This paper cites In- ternational journal of innovative research in computer and communication engineering.

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain In- ternational journal of innovative research in computer and communication engineering

Reference 31

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Observation a3f6eb6e-3fc7-4a97-8f4c-c568e1bf9c92 · outbound

This paper cites DarwinML: A Graph-based Evolutionary Algorithm for Automated Machine Learning.

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain DarwinML: A Graph-based Evolutionary Algorithm for Automated Machine Learning

Reference 32

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Observation b99eb5ae-b384-45e6-8b3a-cc5c28482b5d · outbound

This paper cites Automated Machine Learning with Monte-Carlo Tree Search.

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain Automated Machine Learning with Monte-Carlo Tree Search

Reference 33

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Observation c7aa2415-2b89-418f-ae74-3d748e5cb09f · outbound

This paper cites A quick review of machine learning algorithms.

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain A quick review of machine learning algorithms

Reference 34

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Observation 561ace08-9e82-4bc2-a123-21d0dd27d9b1 · outbound

This paper cites Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks.

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

Reference 35

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Observation fec220fb-5140-49f4-a0f2-150f908f9412 · outbound

This paper cites How to select a suitable machine learning algorithm: A feature-based, scope-oriented selection framework.

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain How to select a suitable machine learning algorithm: A feature-based, scope-oriented selection framework

Reference 36

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Observation e1719e4d-3193-46b3-b744-e26f1567a362 · outbound

This paper cites A review of clustering techniques and developments.Neurocomputing, 267:664–681, 2017.

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain A review of clustering techniques and developments.Neurocomputing, 267:664–681, 2017

Reference 38

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Observation ccafa6d3-197b-4b90-92a0-77a6ebe67ed5 · outbound

This paper cites Estimating the dimension of a model.The annals of statistics, 6(2):461– 464, 1978.

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain Estimating the dimension of a model.The annals of statistics, 6(2):461– 464, 1978

Reference 39

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Observation a1dd1698-356b-439b-9cf5-09f491075a60 · outbound

This paper cites Machine learning map.https://scikit-learn.org/stable/ tutorial/machine_learning_map/index.html, 2020.

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain Machine learning map.https://scikit-learn.org/stable/ tutorial/machine_learning_map/index.html, 2020

Reference 40

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Observation 8ea178f9-77b1-4c90-88ef-99bd56c52316 · outbound

This paper cites Zoomed ranking: Selection of classification algorithms based on relevant performance information.

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain Zoomed ranking: Selection of classification algorithms based on relevant performance information

Reference 41

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Observation 816eb3a7-4916-429a-b643-e3ab8ebfd28b · outbound

This paper cites an unresolved cited work.

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain Unresolved cited work

Reference 42

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Observation 471d0796-830f-4652-ac54-65ecf1734212 · outbound

This paper cites Guidelines to select machine learning scheme for classification of biomedical datasets.

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain Guidelines to select machine learning scheme for classification of biomedical datasets

Reference 43

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Observation 66c7877f-973d-4101-bc2c-d77508139c8e · outbound

This paper cites Auto-weka: Combined selection and hyperparameter optimization of classification algorithms.

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain Auto-weka: Combined selection and hyperparameter optimization of classification algorithms

Reference 44

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Observation 10b8b999-ffec-4af5-bc5b-22ce1ac53fa1 · outbound

This paper cites Automated machine learning in practice: state of the art and recent results.

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain Automated machine learning in practice: state of the art and recent results

Reference 45

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Observation 229a7e74-4f37-4b91-87b1-50e380eb2101 · outbound

This paper cites Hyperparameter importance across datasets.

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain Hyperparameter importance across datasets

Reference 46

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Observation 78bfe01e-a1aa-4202-bd99-11bcb13c98c9 · outbound

This paper cites A novel evolutionary algorithm for automated machine learning focusing on classifier ensem- bles.

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain A novel evolutionary algorithm for automated machine learning focusing on classifier ensem- bles

Reference 47

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