Conditional random mapping for effective ELM feature representation

• Main Authors: Li, Cheng, Deng, Chenwei, Zhou, Shichao, Zhao, Baojun, Huang, Guang-Bin
• Other Authors: School of Electrical and Electronic Engineering
• Format: Article
• Language: English
• Published: 2020
• Subjects: Engineering::Electrical and electronic engineering; Extreme Learning Machine; Conditional Random Feature Mapping
• Online Access: https://hdl.handle.net/10356/141688
• Institution: Nanyang Technological University

Extreme learning machine (ELM) has been extensively studied, due to its fast training and good generalization. Unfortunately, the existing ELM-based feature representation methods are uncompetitive with state-of-the-art deep neural networks (DNNs) when conducting some complex visual recognition task...