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Paper Citation Record · LEDGER

Which Hyperparameters Matter? A Game-Theoretic Framework for Interpretable Hyperparameter Sensitivity Analysis

As of 21 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2607.15884.

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pith.paper-citation-record.v1
2607.15884 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T22:07:32.711236Z

measured 31 of 31 standing notices

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Source: cited_works

Reference resolution

31 of 31 outbound references displayed

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Outbound references

Observation 7658f4c4-7359-49db-a489-66a2de127651 · outbound

This paper cites Hyperparameter Optimization: A Spectral Approach.

Which Hyperparameters Matter? A Game-Theoretic Framework for Interpretable Hyperparameter Sensitivity Analysis Hyperparameter Optimization: A Spectral Approach

Reference 1

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Observation 811c89e3-8a9a-4fd1-88c9-c92e2188902c · outbound

This paper cites Comparative Analysis of Automated Machine Learning for Hyperparameter Opti- mization and Explainable Artificial Intelligence Models,.

Which Hyperparameters Matter? A Game-Theoretic Framework for Interpretable Hyperparameter Sensitivity Analysis Comparative Analysis of Automated Machine Learning for Hyperparameter Opti- mization and Explainable Artificial Intelligence Models,

Reference 2

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Observation 87ad2320-ac88-4e52-9ec1-f66335629c8b · outbound

This paper cites Advanced hyperparameter optimization for improved spatial prediction of shallow landslides using extreme gradient boosting (XGBoost),.

Which Hyperparameters Matter? A Game-Theoretic Framework for Interpretable Hyperparameter Sensitivity Analysis Advanced hyperparameter optimization for improved spatial prediction of shallow landslides using extreme gradient boosting (XGBoost),

Reference 3

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Observation 0c6d1c65-1f13-45d8-9273-a691c9f5018f · outbound

This paper cites ShrinkHPO: Towards Ex- plainable Parallel Hyperparameter Optimization,.

Which Hyperparameters Matter? A Game-Theoretic Framework for Interpretable Hyperparameter Sensitivity Analysis ShrinkHPO: Towards Ex- plainable Parallel Hyperparameter Optimization,

Reference 4

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Observation 8b786afb-ebb0-42f9-bcd0-c7c627279a2e · outbound

This paper cites Hyperparameter Importance Analysis for Multi-Objective AutoML.

Which Hyperparameters Matter? A Game-Theoretic Framework for Interpretable Hyperparameter Sensitivity Analysis Hyperparameter Importance Analysis for Multi-Objective AutoML

Reference 5

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Observation a1a7ec06-93c8-4596-9a47-b880fc5c5726 · outbound

This paper cites Hyperparameter Optimization of Long Short Term Memory Models for Interpretable Electrical Fault Classification,.

Which Hyperparameters Matter? A Game-Theoretic Framework for Interpretable Hyperparameter Sensitivity Analysis Hyperparameter Optimization of Long Short Term Memory Models for Interpretable Electrical Fault Classification,

Reference 6

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Observation d94af9b4-2486-47fe-8ec2-04bd9089e45a · outbound

This paper cites Explaining Bayesian Optimization byShapley Values Facilitates Human-AI Collabo- ration for Exosuit Personalization,.

Which Hyperparameters Matter? A Game-Theoretic Framework for Interpretable Hyperparameter Sensitivity Analysis Explaining Bayesian Optimization byShapley Values Facilitates Human-AI Collabo- ration for Exosuit Personalization,

Reference 7

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Observation 51fc8dcb-5369-404c-8c24-fcc31c59a52a · outbound

This paper cites Explainable Machine Learning for Efficient Diabetes Prediction Using Hyperparame- ter Tuning, SHAP Analysis, Partial Dependency, and LIME,.

Which Hyperparameters Matter? A Game-Theoretic Framework for Interpretable Hyperparameter Sensitivity Analysis Explainable Machine Learning for Efficient Diabetes Prediction Using Hyperparame- ter Tuning, SHAP Analysis, Partial Dependency, and LIME,

Reference 8

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Observation c7f94a2c-2197-4aeb-99d2-2a58e9ea698c · outbound

This paper cites A Survey on Un- certainty Quantification Methods for Deep Learning,.

Which Hyperparameters Matter? A Game-Theoretic Framework for Interpretable Hyperparameter Sensitivity Analysis A Survey on Un- certainty Quantification Methods for Deep Learning,

Reference 9

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Observation 00b80f9b-2138-4791-9994-b52fe9ea35c6 · outbound

This paper cites HyperSHAP: Shapley Values and Interactions for Explaining Hyperparameter Opti- mization,.

Which Hyperparameters Matter? A Game-Theoretic Framework for Interpretable Hyperparameter Sensitivity Analysis HyperSHAP: Shapley Values and Interactions for Explaining Hyperparameter Opti- mization,

Reference 10

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Observation 9bd617fa-8c98-4b6e-b9b7-c41b48040df2 · outbound

This paper cites Comparative SHAP Analysis on SVM and K-NN: Impacts of Hyperparameter Tuning on Model Explainability,.

Which Hyperparameters Matter? A Game-Theoretic Framework for Interpretable Hyperparameter Sensitivity Analysis Comparative SHAP Analysis on SVM and K-NN: Impacts of Hyperparameter Tuning on Model Explainability,

Reference 11

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Observation e2554ab7-2dfb-401c-a143-d8b7358cfe82 · outbound

This paper cites Solutions of Feature and Hyperparameter Model Selection in the Intelligent Manufacturing,.

Which Hyperparameters Matter? A Game-Theoretic Framework for Interpretable Hyperparameter Sensitivity Analysis Solutions of Feature and Hyperparameter Model Selection in the Intelligent Manufacturing,

Reference 12

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Observation b8238a56-ca8a-4c4f-a644-0d6dae69f9f2 · outbound

This paper cites Powershap: A Power-Full Shapley Feature Selection Method,.

Which Hyperparameters Matter? A Game-Theoretic Framework for Interpretable Hyperparameter Sensitivity Analysis Powershap: A Power-Full Shapley Feature Selection Method,

Reference 13

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Observation 6d4f1e73-773c-425e-81b2-1a676135fbac · outbound

This paper cites 17. A Value for n-Person Games,.

Which Hyperparameters Matter? A Game-Theoretic Framework for Interpretable Hyperparameter Sensitivity Analysis 17. A Value for n-Person Games,

Reference 14

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Observation 5674f8b2-9f5c-4736-8f81-369a0444dba6 · outbound

This paper cites shapiq: Shapley Interactions for Machine Learning.

Which Hyperparameters Matter? A Game-Theoretic Framework for Interpretable Hyperparameter Sensitivity Analysis shapiq: Shapley Interactions for Machine Learning

Reference 15

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Observation 777836d3-f630-4634-88b2-04d2b76cc6b0 · outbound

This paper cites Shapley Based Residual Decomposition for Instance Analysis,.

Which Hyperparameters Matter? A Game-Theoretic Framework for Interpretable Hyperparameter Sensitivity Analysis Shapley Based Residual Decomposition for Instance Analysis,

Reference 16

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Observation 9f08616d-73d7-482c-ad58-d9a2cff086c0 · outbound

This paper cites Rethinking data shapley for data selection tasks: misleads and merits,.

Which Hyperparameters Matter? A Game-Theoretic Framework for Interpretable Hyperparameter Sensitivity Analysis Rethinking data shapley for data selection tasks: misleads and merits,

Reference 17

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Observation 4ee05c7a-4a09-4420-aa44-18261398b962 · outbound

This paper cites On Shapley value for measuring importance of dependent inputs.

Which Hyperparameters Matter? A Game-Theoretic Framework for Interpretable Hyperparameter Sensitivity Analysis On Shapley value for measuring importance of dependent inputs

Reference 18

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Observation 4c4293b3-9f38-4cf3-8e1a-b8e9686f78ca · outbound

This paper cites Shapley effects for sen- sitivity analysis with dependent inputs: bootstrap and kriging-based algorithms,.

Which Hyperparameters Matter? A Game-Theoretic Framework for Interpretable Hyperparameter Sensitivity Analysis Shapley effects for sen- sitivity analysis with dependent inputs: bootstrap and kriging-based algorithms,

Reference 19

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Observation fbd0f3d1-7927-4478-98d8-d42ea580852e · outbound

This paper cites Shapley effects for sensitivity analysis with correlated inputs: comparisons with Sobol' indices, numerical estimation and applications.

Which Hyperparameters Matter? A Game-Theoretic Framework for Interpretable Hyperparameter Sensitivity Analysis Shapley effects for sensitivity analysis with correlated inputs: comparisons with Sobol' indices, numerical estimation and applications

Reference 20

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Observation eeca2739-8f10-4120-ac78-d0337d30d51d · outbound

This paper cites Computing Shapley Effects for Sensitivity Analysis,.

Which Hyperparameters Matter? A Game-Theoretic Framework for Interpretable Hyperparameter Sensitivity Analysis Computing Shapley Effects for Sensitivity Analysis,

Reference 21

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Observation 15d34662-e0fe-45e6-8e3b-093a3c677f3f · outbound

This paper cites Shapley Effect Estimation using Polynomial Chaos.

Which Hyperparameters Matter? A Game-Theoretic Framework for Interpretable Hyperparameter Sensitivity Analysis Shapley Effect Estimation using Polynomial Chaos

Reference 22

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Observation 783e03a0-5308-4874-ac32-f65c4b12c1e5 · outbound

This paper cites Uncertainty quantification and global sensitivity analysis with dependent inputs parameters: Application to a basic 2D-hydraulic model,.

Which Hyperparameters Matter? A Game-Theoretic Framework for Interpretable Hyperparameter Sensitivity Analysis Uncertainty quantification and global sensitivity analysis with dependent inputs parameters: Application to a basic 2D-hydraulic model,

Reference 23

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Observation 9252a5ba-7ebf-4262-8f95-99b6a52ebc41 · outbound

This paper cites A Review on Global Sensitivity Analysis Methods,.

Which Hyperparameters Matter? A Game-Theoretic Framework for Interpretable Hyperparameter Sensitivity Analysis A Review on Global Sensitivity Analysis Methods,

Reference 24

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Observation ae53770e-e329-4dc8-bbb1-9c604ad3a473 · outbound

This paper cites Efficient computation of global sensitivity indices using sparse polynomial chaos expansions,.

Which Hyperparameters Matter? A Game-Theoretic Framework for Interpretable Hyperparameter Sensitivity Analysis Efficient computation of global sensitivity indices using sparse polynomial chaos expansions,

Reference 25

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This paper cites Derivative-based Shapley value for global sensitivity analysis and machine learning explainability.

Which Hyperparameters Matter? A Game-Theoretic Framework for Interpretable Hyperparameter Sensitivity Analysis Derivative-based Shapley value for global sensitivity analysis and machine learning explainability

Reference 26

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Observation f8136fc0-c716-4d2f-bf6c-4e69f2cb4fca · outbound

This paper cites Multi-objective optimisation using evolutionary algorithms: an introduction,.

Which Hyperparameters Matter? A Game-Theoretic Framework for Interpretable Hyperparameter Sensitivity Analysis Multi-objective optimisation using evolutionary algorithms: an introduction,

Reference 27

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This paper cites Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations,.

Which Hyperparameters Matter? A Game-Theoretic Framework for Interpretable Hyperparameter Sensitivity Analysis Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations,

Reference 28

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Observation f67c3bc7-3470-4d98-b4d4-528ff05253f0 · outbound

This paper cites Learning multiple layers of features from tiny images,.

Which Hyperparameters Matter? A Game-Theoretic Framework for Interpretable Hyperparameter Sensitivity Analysis Learning multiple layers of features from tiny images,

Reference 29

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This paper cites Adult Dataset,.

Which Hyperparameters Matter? A Game-Theoretic Framework for Interpretable Hyperparameter Sensitivity Analysis Adult Dataset,

Reference 30

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This paper cites Available: https://api.semanticscholar.org/CorpusID: 18268744.

Which Hyperparameters Matter? A Game-Theoretic Framework for Interpretable Hyperparameter Sensitivity Analysis Available: https://api.semanticscholar.org/CorpusID: 18268744

Reference 2009

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