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07/05/2023
On the Adversarial Robustness of Generative Autoencoders in the Latent Space
The generative autoencoders, such as the variational autoencoders or the...
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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 ...
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01/31/2023
Adaptive sparseness for correntropy-based robust regression via automatic relevance determination
Sparseness and robustness are two important properties for many machine ...
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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 (...
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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...
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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...
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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...
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04/22/2022
Multi-view Information Bottleneck Without Variational Approximation
By "intelligently" fusing the complementary information across different...
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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...
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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...
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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 ...
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06/07/2021
Error Loss Networks
A novel model called error loss network (ELN) is proposed to build an er...
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04/21/2020
Robust Motion Averaging under MaximumCorrentropy Criterion
Recently, the motion averaging method has been introduced as an effectiv...
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12/24/2019
Broad Learning System Based on Maximum Correntropy Criterion
As an effective and efficient discriminative learning method, Broad Lear...
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11/21/2019
Asymmetric Correntropy for Robust Adaptive Filtering
In recent years, correntropy has been seccessfully applied to robust ada...
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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 ...
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08/22/2019
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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05/24/2019
Multi-Kernel Correntropy for Robust Learning
As a novel similarity measure that is defined as the expectation of a ke...
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04/14/2019
Minimum Error Entropy Kalman Filter
To date most linear and nonlinear Kalman filters (KFs) have been develop...
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04/13/2019
Maximum Correntropy Criterion with Variable Center
Correntropy is a local similarity measure defined in kernel space and th...
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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...
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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...
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08/07/2018
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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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...
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02/14/2018
Maximum Total Correntropy Diffusion Adaptation over Networks with Noisy Links
Distributed estimation over networks draws much attraction in recent yea...
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02/01/2018
Augmented Space Linear Model
The linear model uses the space defined by the input to project the targ...
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12/03/2017
Diffusion Adaptation Framework for Compressive Sensing Reconstruction
Compressive sensing(CS) has drawn much attention in recent years due to ...
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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...
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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...
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10/11/2017
Quantized Minimum Error Entropy Criterion
Comparing with traditional learning criteria, such as mean square error ...
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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 ...
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03/23/2017
Robustness of Maximum Correntropy Estimation Against Large Outliers
The maximum correntropy criterion (MCC) has recently been successfully a...
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12/21/2016
Robust Learning with Kernel Mean p-Power Error Loss
Correntropy is a second order statistical measure in kernel space, which...
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10/06/2016
Constrained Maximum Correntropy Adaptive Filtering
Constrained adaptive filtering algorithms inculding constrained least me...
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08/26/2016
Maximum Correntropy Unscented Filter
The unscented transformation (UT) is an efficient method to solve the st...
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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...
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02/04/2016
Correntropy Maximization via ADMM - Application to Robust Hyperspectral Unmixing
In hyperspectral images, some spectral bands suffer from low signal-to-n...
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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...
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09/15/2015
Maximum Correntropy Kalman Filter
Traditional Kalman filter (KF) is derived under the well-known minimum m...
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08/08/2015
Diffusion Maximum Correntropy Criterion Algorithms for Robust Distributed Estimation
Robust diffusion adaptive estimation algorithms based on the maximum cor...
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04/12/2015
Generalized Correntropy for Robust Adaptive Filtering
As a robust nonlinear similarity measure in kernel space, correntropy ha...
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01/23/2014
