Surrogate-Assisted Evolutionary Deep Learning Using an End-to-End Random Forest-Based Performance Predictor.
Yanan SunHanding WangBing XueYaochu JinGary G. YenMengjie ZhangPublished in: IEEE Trans. Evol. Comput. (2020)
Keyphrases
- end to end
- random forest
- deep learning
- decision trees
- unsupervised learning
- machine learning
- feature set
- mental models
- genetic algorithm
- ensemble methods
- multi label
- weakly supervised
- congestion control
- neural network
- similarity measure
- image segmentation
- prediction accuracy
- probabilistic model
- base classifiers
- data mining
- data sets