Search Results - subject:"hyperparameter"

Using sequential statistical tests for efficient hyperparameter tuning

Buczak, Philip; Groll, Andreas; Pauly, Markus; Rehof, Jakob - In: AStA Advances in Statistical Analysis 108 (2024) 2, pp. 441-460

Hyperparameter tuning is one of the most time-consuming parts in machine learning. Despite the existence of modern … hyperparameter settings could be discarded after less than k resampling iterations if they are clearly inferior to high … underscore the potential for integrating sequential tests into hyperparameter tuning. …

Persistent link: https://www.econbiz.de/10015361330

Automated machine learning methodology for optimizing production processes in small and medium-sized enterprises

Cruz, Yarens J.; Villalonga, Alberto; Castaño, Fernando; … - In: Operations Research Perspectives 12 (2024), pp. 1-10

Machine learning can be effectively used to generate models capable of representing the dynamic of production processes of small and medium-sized enterprises. These models enable the estimation of key performance indicators, and are often used for optimizing production processes. However, in...

Persistent link: https://www.econbiz.de/10015455378

Job shop scheduling by Deep Dual-Q Network with Prioritized Experience Replay for resilient production control in flexible manufacturing system

Liu, Chao; Chen, Kai; Wang, Hao; Yang, Baojun; Leng, Jiewu - In: Computers & operations research : an international journal 183 (2025), pp. 1-14

Persistent link: https://www.econbiz.de/10015472543

Efficient gasoline spot price prediction using hyperparameter optimization and ensemble machine learning approach

Hamja, Md Amir; Sakib, Md Rakinus; Hasan, Mahmudul; … - In: Machine Learning Technologies on Energy Economics and …, (pp. 285-313). 2025

Persistent link: https://www.econbiz.de/10015450336

A linear programming-based hyper local search for tuning hyperparameters

Sinha, Ankur; Gunwal, Satender - In: Operations research letters : a journal of INFORMS … 61 (2025), pp. 1-10

Persistent link: https://www.econbiz.de/10015432120

On the equivalence and performance of distributionally robust optimization and robust satisficing models

Wang, Zhiyuan; Ran, Lun; Zhou, Minglong; He, Long - In: Manufacturing & service operations management : M & SOM 27 (2025) 4, pp. 1295-1312

Persistent link: https://www.econbiz.de/10015433273

A transparent alternative to neural networks with an application to predicting volatility

Czasonis, Megan; Kritzman, Mark; Turkington, David - In: Journal of investment management : JOIM 23 (2025) 3, pp. 4-17

Persistent link: https://www.econbiz.de/10015651839

The efficiency of various types of input layers of LSTM model in investment strategies on S&P500 index

Thi Thu Giang Nguyen; Ślepaczuk, Robert - 2022

Persistent link: https://www.econbiz.de/10013474013

Comparison of algorithms for error prediction in manufacturing with automl and a cost-based metric

Gerling, Alexander; Ziekow, Holger; Hess, Andreas; … - In: Journal of Intelligent Manufacturing 33 (2022) 2, pp. 555-573

RandomSearchCV and HyperOpt hyperparameter tuning. The algorithms are optimized based on multiple metrics, which we will introduce in …

Persistent link: https://www.econbiz.de/10015166371

Bilevel hyperparameter optimization for support vector classification : theoretical analysis and a solution method

Li, Qingna; Li, Zhen; Zemkoho, Alain B. - In: Mathematical methods of operations research : ZOR 96 (2022) 3, pp. 315-350

Persistent link: https://www.econbiz.de/10013455088