scholarly journals An ensemble learning framework for distributed resource allocation in inteference channels: The two user case

George A. Ropokis
Synlett ◽  
2020 ◽  
Akira Yada ◽  
Kazuhiko Sato ◽  
Tarojiro Matsumura ◽  
Yasunobu Ando ◽  
Kenji Nagata ◽  

AbstractThe prediction of the initial reaction rate in the tungsten-catalyzed epoxidation of alkenes by using a machine learning approach is demonstrated. The ensemble learning framework used in this study consists of random sampling with replacement from the training dataset, the construction of several predictive models (weak learners), and the combination of their outputs. This approach enables us to obtain a reasonable prediction model that avoids the problem of overfitting, even when analyzing a small dataset.

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 3675-3693 ◽  
Salman Salloum ◽  
Joshua Zhexue Huang ◽  
Yulin He ◽  
Xiaojun Chen

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