Hyperparameter Importance Across Datasets - researchr publication related

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Jan N. van Rijn, Frank Hutter. Hyperparameter Importance Across Datasets. In Yike Guo, Faisal Farooq, editors, Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, KDD 2018, London, UK, August 19-23, 2018. pages 2367-2376, ACM, 2018. [doi]

The following publications are possibly variants of this publication:

An Empirical Study of Hyperparameter Importance Across DatasetsJan N. van Rijn, Frank Hutter. pkdd 2017: 91-98 [doi]

Hyperparameter Importance of Quantum Neural Networks Across Small DatasetsCharles Moussa, Jan N. van Rijn, Thomas Bäck, Vedran Dunjko. dis 2022: 32-46 [doi]

Hyperparameter importance and optimization of quantum neural networks across small datasetsCharles Moussa, Yash J. Patel, Vedran Dunjko, Thomas Bäck, Jan N. van Rijn. ml, 113(4):1941-1966, April 2024. [doi]

An Efficient Approach for Assessing Hyperparameter ImportanceFrank Hutter, Holger Hoos, Kevin Leyton-Brown. icml 2014: 754-762 [doi]

On the Importance of Hyperparameter Optimization for Model-based Reinforcement LearningBaohe Zhang, Raghu Rajan, Luis-Pineda, Nathan O. Lambert, André Biedenkapp, Kurtland Chua, Frank Hutter, Roberto Calandra. aistats 2021: 4015-4023 [doi]

Hyperparameter Importance for Image Classification by Residual Neural NetworksAbhinav Sharma, Jan N. van Rijn, Frank Hutter, Andreas Müller. dis 2019: 112-126 [doi]

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