Search Results for author: Badong Chen

Found 40 papers, 1 papers with code

Gate Recurrent Unit Network based on Hilbert-Schmidt Independence Criterion for State-of-Health Estimation

no code implementations16 Mar 2023 Ziyue Huang, Lujuan Dang, Yuqing Xie, Wentao Ma, Badong Chen

State-of-health (SOH) estimation is a key step in ensuring the safe and reliable operation of batteries.

Adaptive sparseness for correntropy-based robust regression via automatic relevance determination

no code implementations31 Jan 2023 Yuanhao Li, Badong Chen, Okito Yamashita, Natsue Yoshimura, Yasuharu Koike

In the present study, regarding the maximum correntropy criterion (MCC) based robust regression algorithm, we investigate to integrate the MCC method with the automatic relevance determination (ARD) technique in a Bayesian framework, so that MCC-based robust regression could be implemented with adaptive sparseness.

Bayesian Inference feature selection +1

CI-GNN: A Granger Causality-Inspired Graph Neural Network for Interpretable Brain Network-Based Psychiatric Diagnosis

no code implementations4 Jan 2023 Kaizhong Zheng, Shujian Yu, Badong Chen

There is a recent trend to leverage the power of graph neural networks (GNNs) for brain-network based psychiatric diagnosis, which, in turn, also motivates an urgent need for psychiatrists to fully understand the decision behavior of the used GNNs.

Study of General Robust Subband Adaptive Filtering

no code implementations4 Aug 2022 Yi Yu, Hongsen He, Rodrigo C. de Lamare, Badong Chen

In this paper, we propose a general robust subband adaptive filtering (GR-SAF) scheme against impulsive noise by minimizing the mean square deviation under the random-walk model with individual weight uncertainty.

Correntropy-Based Logistic Regression with Automatic Relevance Determination for Robust Sparse Brain Activity Decoding

no code implementations20 Jul 2022 Yuanhao Li, Badong Chen, Yuxi Shi, Natsue Yoshimura, Yasuharu Koike

To this end, we introduce the correntropy learning framework into the automatic relevance determination based sparse classification model, proposing a new correntropy-based robust sparse logistic regression algorithm.

Brain Decoding Classification +2

Counting Varying Density Crowds Through Density Guided Adaptive Selection CNN and Transformer Estimation

no code implementations21 Jun 2022 Yuehai Chen, Jing Yang, Badong Chen, Shaoyi Du

Thus, CNN could locate and estimate crowds accurately in low-density regions, while it is hard to properly perceive the densities in high-density regions.

Crowd Counting

BrainIB: Interpretable Brain Network-based Psychiatric Diagnosis with Graph Information Bottleneck

no code implementations7 May 2022 Kaizhong Zheng, Shujian Yu, Baojuan Li, Robert Jenssen, Badong Chen

Developing a new diagnostic models based on the underlying biological mechanisms rather than subjective symptoms for psychiatric disorders is an emerging consensus.

Multi-view Information Bottleneck Without Variational Approximation

1 code implementation22 Apr 2022 Qi Zhang, Shujian Yu, Jingmin Xin, Badong Chen

By "intelligently" fusing the complementary information across different views, multi-view learning is able to improve the performance of classification tasks.


Active noise control techniques for nonlinear systems

no code implementations19 Oct 2021 Lu Lu, Kai-Li Yin, Rodrigo C. de Lamare, Zongsheng Zheng, Yi Yu, Xiaomin Yang, Badong Chen

Most of the literature focuses on the development of the linear active noise control (ANC) techniques.

A survey on active noise control techniques -- Part I: Linear systems

no code implementations1 Oct 2021 Lu Lu, Kai-Li Yin, Rodrigo C. de Lamare, Zongsheng Zheng, Yi Yu, Xiaomin Yang, Badong Chen

Active noise control (ANC) is an effective way for reducing the noise level in electroacoustic or electromechanical systems.

Region-Aware Network: Model Human's Top-Down Visual Perception Mechanism for Crowd Counting

no code implementations23 Jun 2021 Yuehai Chen, Jing Yang, Dong Zhang, Kun Zhang, Badong Chen, Shaoyi Du

More specifically, we scan the whole input images and its priority maps in the form of column vector to obtain a relevance matrix estimating their similarity.

Crowd Counting

Error Loss Networks

no code implementations7 Jun 2021 Badong Chen, Yunfei Zheng, Pengju Ren

A novel model called error loss network (ELN) is proposed to build an error loss function for supervised learning.

Robust Motion Averaging under Maximum Correntropy Criterion

no code implementations21 Apr 2020 Jihua Zhu, Jie Hu, Huimin Lu, Badong Chen, Zhongyu Li

Recently, the motion averaging method has been introduced as an effective means to solve the multi-view registration problem.

Broad Learning System Based on Maximum Correntropy Criterion

no code implementations24 Dec 2019 Yunfei Zheng, Badong Chen, Shiyuan Wang, Senior Member, Weiqun Wang, Member, IEEE

As an effective and efficient discriminative learning method, Broad Learning System (BLS) has received increasing attention due to its outstanding performance in various regression and classification problems.

General Classification Incremental Learning +1

Asymmetric Correntropy for Robust Adaptive Filtering

no code implementations21 Nov 2019 Badong Chen, Yuqing Xie, Zhuang Li, Yingsong Li, Pengju Ren

Correntropy is generally defined as the expectation of a Gaussian kernel between two random variables.

Restricted Minimum Error Entropy Criterion for Robust Classification

no code implementations6 Sep 2019 Yuanhao Li, Badong Chen, Natsue Yoshimura, Yasuharu Koike

The minimum error entropy (MEE) criterion has been verified as a powerful approach for non-Gaussian signal processing and robust machine learning.

Classification Dimensionality Reduction +3

An encoding framework with brain inner state for natural image identification

no code implementations22 Aug 2019 Hao Wu, Ziyu Zhu, Jiayi Wang, Nanning Zheng, Badong Chen

The framework comprises two parts: forward encoding model that deals with visual stimuli and inner state model that captures influence from intrinsic connections in the brain.

Brain Decoding

Multi-Kernel Correntropy for Robust Learning

no code implementations24 May 2019 Badong Chen, Yuqing Xie, Xin Wang, Zejian yuan, Pengju Ren, Jing Qin

In a recent work, the concept of mixture correntropy (MC) was proposed to improve the learning performance, where the kernel function is a mixture Gaussian kernel, namely a linear combination of several zero-mean Gaussian kernels with different widths.

Maximum Correntropy Criterion with Variable Center

no code implementations13 Apr 2019 Badong Chen, Xin Wang, Yingsong Li, Jose C. Principe

The kernel function in correntropy is usually restricted to the Gaussian function with center located at zero.

Consistency-aware Shading Orders Selective Fusion for Intrinsic Image Decomposition

no code implementations23 Oct 2018 Yuanliu Liu, Ang Li, Zejian yuan, Badong Chen, Nanning Zheng

We propose a Consistency-aware Selective Fusion (CSF) to integrate the pairwise orders into a globally consistent order.

Intrinsic Image Decomposition

Prognostics Estimations with Dynamic States

no code implementations16 Jul 2018 Rong-Jing Bao, Hai-Jun Rong, Zhi-Xin Yang, Badong Chen

The health state assessment and remaining useful life (RUL) estimation play very important roles in prognostics and health management (PHM), owing to their abilities to reduce the maintenance and improve the safety of machines or equipment.


Augmented Space Linear Model

no code implementations1 Feb 2018 Zhengda Qin, Badong Chen, Nanning Zheng, Jose C. Principe

In this paper, we propose a linear model called Augmented Space Linear Model (ASLM), which uses the full joint space of input and desired signal as the projection space and approaches the performance of nonlinear models.

A Novel Brain Decoding Method: a Correlation Network Framework for Revealing Brain Connections

no code implementations1 Dec 2017 Siyu Yu, Nanning Zheng, Yongqiang Ma, Hao Wu, Badong Chen

Analyzing the correlations of collected data from human brain activities and representing activity patterns are two problems in brain decoding based on functional magnetic resonance imaging (fMRI) signals.

Brain Decoding

Bias-Compensated Normalized Maximum Correntropy Criterion Algorithm for System Identification with Noisy Input

no code implementations23 Nov 2017 Wentao Ma, Dongqiao Zheng, Yuanhao Li, ZhiYu Zhang, Badong Chen

This paper proposed a bias-compensated normalized maximum correntropy criterion (BCNMCC) algorithm charactered by its low steady-state misalignment for system identification with noisy input in an impulsive output noise environment.

Quantized Minimum Error Entropy Criterion

no code implementations11 Oct 2017 Badong Chen, Lei Xing, Nanning Zheng, Jose C. Príncipe

Comparing with traditional learning criteria, such as mean square error (MSE), the minimum error entropy (MEE) criterion is superior in nonlinear and non-Gaussian signal processing and machine learning.


Associations among Image Assessments as Cost Functions in Linear Decomposition: MSE, SSIM, and Correlation Coefficient

no code implementations4 Aug 2017 Jianji Wang, Nanning Zheng, Badong Chen, Jose C. Principe

Moreover, for a target vector, the ratio of the corresponding affine parameters in the MSE-based linear decomposition scheme and the SSIM-based scheme is a constant, which is just the value of PCC between the target vector and its estimated vector.


Robustness of Maximum Correntropy Estimation Against Large Outliers

no code implementations23 Mar 2017 Badong Chen, Lei Xing, Haiquan Zhao, Bin Xu, Jose C. Principe

The maximum correntropy criterion (MCC) has recently been successfully applied in robust regression, classification and adaptive filtering, where the correntropy is maximized instead of minimizing the well-known mean square error (MSE) to improve the robustness with respect to outliers (or impulsive noises).

Robust Learning with Kernel Mean p-Power Error Loss

no code implementations21 Dec 2016 Badong Chen, Lei Xing, Xin Wang, Jing Qin, Nanning Zheng

Correntropy is a second order statistical measure in kernel space, which has been successfully applied in robust learning and signal processing.

Constrained Maximum Correntropy Adaptive Filtering

no code implementations6 Oct 2016 Siyuan Peng, Badong Chen, Lei Sun, Zhiping Lin, Wee Ser

Most existing constrained adaptive filtering algorithms are developed under mean square error (MSE) criterion, which is an ideal optimality criterion under Gaussian noises.

Maximum Correntropy Unscented Filter

no code implementations26 Aug 2016 Xi Liu, Badong Chen, Bin Xu, Zongze Wu, Paul Honeine

To improve the robustness of the UKF against impulsive noises, a new filter for nonlinear systems is proposed in this work, namely the maximum correntropy unscented filter (MCUF).

Kernel Risk-Sensitive Loss: Definition, Properties and Application to Robust Adaptive Filtering

no code implementations1 Aug 2016 Badong Chen, Lei Xing, Bin Xu, Haiquan Zhao, Nanning Zheng, Jose C. Principe

Nonlinear similarity measures defined in kernel space, such as correntropy, can extract higher-order statistics of data and offer potentially significant performance improvement over their linear counterparts especially in non-Gaussian signal processing and machine learning.

Similarity Learning With Spatial Constraints for Person Re-Identification

no code implementations CVPR 2016 Dapeng Chen, Zejian yuan, Badong Chen, Nanning Zheng

We therefore learn a novel similarity function, which consists of multiple sub-similarity measurements with each taking in charge of a subregion.

Person Re-Identification

Correntropy Maximization via ADMM - Application to Robust Hyperspectral Unmixing

no code implementations4 Feb 2016 Fei Zhu, Abderrahim Halimi, Paul Honeine, Badong Chen, Nanning Zheng

In hyperspectral images, some spectral bands suffer from low signal-to-noise ratio due to noisy acquisition and atmospheric effects, thus requiring robust techniques for the unmixing problem.

Hyperspectral Unmixing

Illumination Robust Color Naming via Label Propagation

no code implementations ICCV 2015 Yuanliu liu, Zejian yuan, Badong Chen, Jianru Xue, Nanning Zheng

In this paper we address the problem of inferring the color composition of the intrinsic reflectance of objects, where the shadows and highlights may change the observed color dramatically.

Image Retrieval Retrieval

Maximum Correntropy Kalman Filter

no code implementations15 Sep 2015 Badong Chen, Xi Liu, Haiquan Zhao, José C. Príncipe

Traditional Kalman filter (KF) is derived under the well-known minimum mean square error (MMSE) criterion, which is optimal under Gaussian assumption.

Diffusion Maximum Correntropy Criterion Algorithms for Robust Distributed Estimation

no code implementations8 Aug 2015 Wentao Ma, Badong Chen, Jiandong Duan, Haiquan Zhao

Robust diffusion adaptive estimation algorithms based on the maximum correntropy criterion (MCC), including adaptation to combination MCC and combination to adaptation MCC, are developed to deal with the distributed estimation over network in impulsive (long-tailed) noise environments.

Generalized Correntropy for Robust Adaptive Filtering

no code implementations12 Apr 2015 Badong Chen, Lei Xing, Haiquan Zhao, Nanning Zheng, José C. Príncipe

In this work, we propose a generalized correntropy that adopts the generalized Gaussian density (GGD) function as the kernel (not necessarily a Mercer kernel), and present some important properties.

Kernel Least Mean Square with Adaptive Kernel Size

no code implementations23 Jan 2014 Badong Chen, Junli Liang, Nanning Zheng, Jose C. Principe

Kernel adaptive filters (KAF) are a class of powerful nonlinear filters developed in Reproducing Kernel Hilbert Space (RKHS).

Time Series Prediction

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