
Broad Learning System Based on Maximum Correntropy Criterion
As an effective and efficient discriminative learning method, Broad Lear...
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An encoding framework with brain inner state for natural image identification
Neural encoding and decoding, which aim to characterize the relationship...
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Consistencyaware Shading Orders Selective Fusion for Intrinsic Image Decomposition
We address the problem of decomposing a single image into reflectance an...
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BiasCompensated Normalized Maximum Correntropy Criterion Algorithm for System Identification with Noisy Input
This paper proposed a biascompensated normalized maximum correntropy cr...
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Quantized Minimum Error Entropy Criterion
Comparing with traditional learning criteria, such as mean square error ...
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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 ...
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Robustness of Maximum Correntropy Estimation Against Large Outliers
The maximum correntropy criterion (MCC) has recently been successfully a...
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Robust Learning with Kernel Mean pPower Error Loss
Correntropy is a second order statistical measure in kernel space, which...
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Constrained Maximum Correntropy Adaptive Filtering
Constrained adaptive filtering algorithms inculding constrained least me...
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Maximum Correntropy Unscented Filter
The unscented transformation (UT) is an efficient method to solve the st...
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Kernel RiskSensitive Loss: Definition, Properties and Application to Robust Adaptive Filtering
Nonlinear similarity measures defined in kernel space, such as correntro...
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Maximum Correntropy Kalman Filter
Traditional Kalman filter (KF) is derived under the wellknown minimum m...
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Diffusion Maximum Correntropy Criterion Algorithms for Robust Distributed Estimation
Robust diffusion adaptive estimation algorithms based on the maximum cor...
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Generalized Correntropy for Robust Adaptive Filtering
As a robust nonlinear similarity measure in kernel space, correntropy ha...
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Correntropy Maximization via ADMM  Application to Robust Hyperspectral Unmixing
In hyperspectral images, some spectral bands suffer from low signalton...
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Kernel Least Mean Square with Adaptive Kernel Size
Kernel adaptive filters (KAF) are a class of powerful nonlinear filters ...
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Diffusion Adaptation Framework for Compressive Sensing Reconstruction
Compressive sensing(CS) has drawn much attention in recent years due to ...
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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...
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Augmented Space Linear Model
The linear model uses the space defined by the input to project the targ...
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Maximum Total Correntropy Diffusion Adaptation over Networks with Noisy Links
Distributed estimation over networks draws much attraction in recent yea...
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Two improved normalized subband adaptive filter algorithms with good robustness against impulsive interferences
To improve the robustness of subband adaptive filter (SAF) against impul...
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Remaining Useful Life Estimation of AeroEngines with SelfJoint Prediction of Continuous and Discrete States
The remaining useful life (RUL) estimation generally suffer from this pr...
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Granger Causality Analysis Based on Quantized Minimum Error Entropy Criterion
Linear regression model (LRM) based on mean square error (MSE) criterion...
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Minimum Error Entropy Kalman Filter
To date most linear and nonlinear Kalman filters (KFs) have been develop...
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Robust Matrix Completion via Maximum Correntropy Criterion and Half Quadratic Optimization
Robust matrix completion aims to recover a lowrank matrix from a subset...
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Maximum Correntropy Criterion with Variable Center
Correntropy is a local similarity measure defined in kernel space and th...
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MultiKernel Correntropy for Robust Learning
As a novel similarity measure that is defined as the expectation of a ke...
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Robust Logistic Regression against Attribute and Label Outliers via Information Theoretic Learning
The framework of information theoretic learning (ITL) has been verified ...
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Asymmetric Correntropy for Robust Adaptive Filtering
In recent years, correntropy has been seccessfully applied to robust ada...
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Robust Motion Averaging under MaximumCorrentropy Criterion
Recently, the motion averaging method has been introduced as an effectiv...
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Badong Chen
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PhD, Professor Institute of Artificial Intelligence and Robotics Dept. of Automation Science and Technology School of Electronic and Inform. Engineering at Xi'an Jiaotong University