Stacked Denoising Extreme Learning Machine Autoencoder Based on Graph Embedding for Feature Representation
Extreme learning machine is characterized by less training parameters, fast training speed, and strong generalization ability. It has been applied to obtain feature representations from the complex data in the tasks of data clustering or classification. In this paper, a graph embedding-based denoisi...
Main Authors: | Hongwei Ge, Weiting Sun, Mingde Zhao, Yao Yao |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2019-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/8620205/ |
Similar Items
-
Clustering Mixed Data Based on Density Peaks and Stacked Denoising Autoencoders
by: Baobin Duan, et al.
Published: (2019-02-01) -
Remote Sensing Image Classification Based on Stacked Denoising Autoencoder
by: Peng Liang, et al.
Published: (2017-12-01) -
Sparsity-Penalized Stacked Denoising Autoencoders for Imputing Single-Cell RNA-Seq Data
by: Weilai Chi, et al.
Published: (2020-05-01) -
Leveraging Wearable Sensors for Human Daily Activity Recognition with Stacked Denoising Autoencoders
by: Qin Ni, et al.
Published: (2020-09-01) -
A Novel Stacked Denoising Autoencoder-Based Reconstruction Framework for Cerenkov Luminescence Tomography
by: Xin Cao, et al.
Published: (2019-01-01)