b'Badong Chen'

research

∙ 07/05/2023

On the Adversarial Robustness of Generative Autoencoders in the Latent Space

The generative autoencoders, such as the variational autoencoders or the...

0 Mingfei Lu, et al. ∙

research

∙ 03/16/2023

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

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

0 Ziyue Huang, et al. ∙

research

∙ 01/31/2023

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

Sparseness and robustness are two important properties for many machine ...

0 Yuanhao Li, et al. ∙

research

∙ 01/04/2023

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

There is a recent trend to leverage the power of graph neural networks (...

0 Kaizhong Zheng, et al. ∙

research

∙ 07/20/2022

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

Recent studies have utilized sparse classifications to predict categoric...

0 Yuanhao Li, et al. ∙

research

∙ 06/21/2022

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

In real-world crowd counting applications, the crowd densities in an ima...

0 Yuehai Chen, et al. ∙

research

∙ 05/07/2022

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

Developing a new diagnostic models based on the underlying biological me...

0 Kaizhong Zheng, et al. ∙

research

∙ 04/22/2022

Multi-view Information Bottleneck Without Variational Approximation

By "intelligently" fusing the complementary information across different...

0 Qi Zhang, et al. ∙

research

∙ 10/19/2021

A survey on active noise control techniques – Part II: Nonlinear systems

Part I of this paper reviewed the development of the linear active noise...

0 Lu Lu, et al. ∙

research

∙ 10/01/2021

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

Active noise control (ANC) is an effective way for reducing the noise le...

0 Lu Lu, et al. ∙

research

∙ 06/23/2021

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

Background noise and scale variation are common problems that have been ...

0 Yuehai Chen, et al. ∙

research

∙ 06/07/2021

Error Loss Networks

A novel model called error loss network (ELN) is proposed to build an er...

0 Badong Chen, et al. ∙

research

∙ 04/21/2020

Robust Motion Averaging under MaximumCorrentropy Criterion

Recently, the motion averaging method has been introduced as an effectiv...

0 Jihua Zhu, et al. ∙

research

∙ 12/24/2019

Broad Learning System Based on Maximum Correntropy Criterion

As an effective and efficient discriminative learning method, Broad Lear...

43 Yunfei Zheng, et al. ∙

research

∙ 11/21/2019

Asymmetric Correntropy for Robust Adaptive Filtering

In recent years, correntropy has been seccessfully applied to robust ada...

0 Badong Chen, et al. ∙

research

∙ 09/06/2019

Robust Logistic Regression against Attribute and Label Outliers via Information Theoretic Learning

The framework of information theoretic learning (ITL) has been verified ...

0 Yuanhao Li, et al. ∙

research

∙ 08/22/2019

An encoding framework with brain inner state for natural image identification

Neural encoding and decoding, which aim to characterize the relationship...

4 Hao Wu, et al. ∙

research

∙ 05/24/2019

Multi-Kernel Correntropy for Robust Learning

As a novel similarity measure that is defined as the expectation of a ke...

0 Badong Chen, et al. ∙

research

∙ 04/14/2019

Minimum Error Entropy Kalman Filter

To date most linear and nonlinear Kalman filters (KFs) have been develop...

0 Badong Chen, et al. ∙

research

∙ 04/13/2019

Maximum Correntropy Criterion with Variable Center

Correntropy is a local similarity measure defined in kernel space and th...

0 Badong Chen, et al. ∙

research

∙ 03/14/2019

Robust Matrix Completion via Maximum Correntropy Criterion and Half Quadratic Optimization

Robust matrix completion aims to recover a low-rank matrix from a subset...

0 Yicong He, et al. ∙

research

∙ 10/23/2018

Consistency-aware Shading Orders Selective Fusion for Intrinsic Image Decomposition

We address the problem of decomposing a single image into reflectance an...

2 Yuanliu Liu, et al. ∙

research

∙ 08/07/2018

Granger Causality Analysis Based on Quantized Minimum Error Entropy Criterion

Linear regression model (LRM) based on mean square error (MSE) criterion...

0 Badong Chen, et al. ∙

research

∙ 07/16/2018

Remaining Useful Life Estimation of Aero-Engines with Self-Joint Prediction of Continuous and Discrete States

The remaining useful life (RUL) estimation generally suffer from this pr...

0 Rong-Jing Bao, et al. ∙

research

∙ 02/14/2018

Maximum Total Correntropy Diffusion Adaptation over Networks with Noisy Links

Distributed estimation over networks draws much attraction in recent yea...

0 Yicong He, et al. ∙

research

∙ 02/01/2018

Augmented Space Linear Model

The linear model uses the space defined by the input to project the targ...

0 Zhengda Qin, et al. ∙

research

∙ 12/03/2017

Diffusion Adaptation Framework for Compressive Sensing Reconstruction

Compressive sensing(CS) has drawn much attention in recent years due to ...

0 Yicong He, et al. ∙

research

∙ 12/01/2017

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

Brain decoding is a hot spot in cognitive science, which focuses on reco...

0 Siyu Yu, et al. ∙

research

∙ 11/23/2017

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

This paper proposed a bias-compensated normalized maximum correntropy cr...

0 Wentao Ma, et al. ∙

research

∙ 10/11/2017

Quantized Minimum Error Entropy Criterion

Comparing with traditional learning criteria, such as mean square error ...

0 Badong Chen, et al. ∙

research

∙ 08/04/2017

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

The traditional methods of image assessment, such as mean squared error ...

0 Jianji Wang, et al. ∙

research

∙ 03/23/2017

Robustness of Maximum Correntropy Estimation Against Large Outliers

The maximum correntropy criterion (MCC) has recently been successfully a...

0 Badong Chen, et al. ∙

research

∙ 12/21/2016

Robust Learning with Kernel Mean p-Power Error Loss

Correntropy is a second order statistical measure in kernel space, which...

0 Badong Chen, et al. ∙

research

∙ 10/06/2016

Constrained Maximum Correntropy Adaptive Filtering

Constrained adaptive filtering algorithms inculding constrained least me...

0 Siyuan Peng, et al. ∙

research

∙ 08/26/2016

Maximum Correntropy Unscented Filter

The unscented transformation (UT) is an efficient method to solve the st...

0 Xi Liu, et al. ∙

research

∙ 08/01/2016

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

Nonlinear similarity measures defined in kernel space, such as correntro...

0 Badong Chen, et al. ∙

research

∙ 02/04/2016

Correntropy Maximization via ADMM - Application to Robust Hyperspectral Unmixing

In hyperspectral images, some spectral bands suffer from low signal-to-n...

0 Fei Zhu, et al. ∙

research

∙ 12/16/2015

Two improved normalized subband adaptive filter algorithms with good robustness against impulsive interferences

To improve the robustness of subband adaptive filter (SAF) against impul...

0 Yi Yu, et al. ∙

research

∙ 09/15/2015

Maximum Correntropy Kalman Filter

Traditional Kalman filter (KF) is derived under the well-known minimum m...

0 Badong Chen, et al. ∙

research

∙ 08/08/2015

Diffusion Maximum Correntropy Criterion Algorithms for Robust Distributed Estimation

Robust diffusion adaptive estimation algorithms based on the maximum cor...

0 Wentao Ma, et al. ∙

research

∙ 04/12/2015

Generalized Correntropy for Robust Adaptive Filtering

As a robust nonlinear similarity measure in kernel space, correntropy ha...

0 Badong Chen, et al. ∙

research

∙ 01/23/2014

Kernel Least Mean Square with Adaptive Kernel Size

Kernel adaptive filters (KAF) are a class of powerful nonlinear filters ...

0 Badong Chen, et al. ∙

Badong Chen

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