780 citations · 1.6k across the 54 of their papers we have counts for
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Broad Learning System Based on Maximum Correntropy Criterion
Yunfei Zheng, Badong Chen, Shiyuan Wang +1
As an effective and efficient discriminative learning method, Broad Learning System (BLS) has received increasing attention due to its outstanding performance in various regression…
Asymmetric Correntropy for Robust Adaptive Filtering
Badong Chen, Yuqing Xie, Zhuang Li +2
In recent years, correntropy has been seccessfully applied to robust adaptive filtering to eliminate adverse effects of impulsive noises or outliers. Correntropy is generally defin…
Restricted Minimum Error Entropy Criterion for Robust Classification
Yuanhao Li, Badong Chen, Natsue Yoshimura +1
The minimum error entropy (MEE) criterion has been verified as a powerful approach for non-Gaussian signal processing and robust machine learning. However, the implementation of ME…
An encoding framework with brain inner state for natural image identification
Hao Wu, Ziyu Zhu, Jiayi Wang +2
Neural encoding and decoding, which aim to characterize the relationship between stimuli and brain activities, have emerged as an important area in cognitive neuroscience. Traditio…
Multi-Kernel Correntropy for Robust Learning
Badong Chen, Yuqing Xie, Xin Wang +3
As a novel similarity measure that is defined as the expectation of a kernel function between two random variables, correntropy has been successfully applied in robust machine lear…
Minimum Error Entropy Kalman Filter
Badong Chen, Lujuan Dang, Yuantao Gu +2
To date most linear and nonlinear Kalman filters (KFs) have been developed under the Gaussian assumption and the well-known minimum mean square error (MMSE) criterion. In order to…