Extreme Learning Machines on High Dimensional and Large Data Applications: A Survey
Extreme learning machine (ELM) has been developed for single hidden layer feedforward neural networks (SLFNs). In ELM algorithm, the connections between the input layer and the hidden neurons are randomly assigned and remain unchanged during the learning process. The output connections are then tune...
Saved in:
Main Authors: | Cao, Jiuwen, Lin, Zhiping |
---|---|
其他作者: | School of Electrical and Electronic Engineering |
格式: | Article |
語言: | English |
出版: |
2015
|
在線閱讀: | https://hdl.handle.net/10356/104321 http://hdl.handle.net/10220/38820 |
標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|
機構: | Nanyang Technological University |
語言: | English |
相似書籍
-
Voting based extreme learning machine
由: Cao, Jiuwen, et al.
出版: (2013) -
Voting base online sequential extreme learning machine for multi-class classification
由: Cao, Jiuwen, et al.
出版: (2013) -
Further studies of extreme learning machine and compressed signal detection
由: Cao, Jiuwen
出版: (2013) -
Extreme learning machine with affine transformation inputs in an activation function
由: Cao, Jiuwen, et al.
出版: (2020) -
Ensemble-Based Risk Scoring with Extreme Learning Machine for Prediction of Adverse Cardiac Events
由: Liu, Nan, et al.
出版: (2018)