Results 121 to 130 of about 111,316 (150)

Transfer Learning and Ensemble Learning

2020
In this chapter, we start from transfer learning and introduce the relationship between different learners; we use ensemble learning to combine them together and hope to get a strong learner from a weak learner by changing the training dataset or adjusting parameters of networks. Our ultimate goal is to implement a robust and stable classifier.
openaire   +1 more source

Ensemble Learning

2021
Jitendra Kumar, Ashutosh Kumar Singh, Anand Mohan, Rajkumar Buyya   +3 more
openaire   +2 more sources

Ensemble deep learning: A review

Engineering Applications of Artificial Intelligence, 2022
M A Ganaie, Minghui Hu, A K Malik
exaly  

Evolutionary bagging for ensemble learning

Neurocomputing, 2022
Rohitash Chandra
exaly  

Ensemble Learning

2023
  +4 more sources

Ensemble Learning

Ian H. Witten, Eibe Frank, Mark A. Hall, Christopher J. Pal, James R. Foulds   +4 more
  +8 more sources

Ensemble learning framework for landslide susceptibility mapping: Different basic classifier and ensemble strategy

Geoscience Frontiers, 2023
Taorui Zeng, Thomas Glade, Yuichi S Hayakawa   +2 more
exaly  

Ensemble learning-based classification models for slope stability analysis

Catena, 2021
Khanh Pham, Dongku Kim, Sangyeong Park   +2 more
exaly  

A Survey on Ensemble Learning for Data Stream Classification

ACM Computing Surveys, 2018
Heitor Murilo Gomes, Jean Paul Barddal, Fabricio Enembreck   +2 more
exaly  

Deep convolutional neural networks with ensemble learning and transfer learning for capacity estimation of lithium-ion batteries

Applied Energy, 2020
Sheng Shen, Mohammadkazem Sadoughi, Zhengdao Wang   +2 more
exaly