Results 11 to 20 of about 1,526 (199)
ADMM for maximum correntropy criterion [PDF]
2016 International Joint Conference on Neural Networks (IJCNN), 2016 The correntropy provides a robust criterion for outlier-insensitive machine learning, and its maximisation has been increasingly investigated in signal and image processing. In this paper, we investigate the problem of unmixing hyperspectral images, namely decomposing each pixel/spectrum of a given image as a linear combination of other pixels/spectra ...
Zhu, Fei +4 more
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The Fast Correntropy Mace Filter [PDF]
2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07, 2007 In this paper, we implement the newly introduced correntropy MACE filter using the fast Gauss transform (FGT). The correntropy MACE filter is a nonlinear extension to the MACE filter using the correntropy function in a feature space nonlinearly related to the input. The correntropy MACE outperforms the traditional linear MACE in both generalization and
Kyu-Hwa Jeong +2 more
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Regularized maximum correntropy machine [PDF]
Neurocomputing, 2015 In this paper we investigate the usage of regularized correntropy framework for learning of classifiers from noisy labels. The class label predictors learned by minimizing transitional loss functions are sensitive to the noisy and outlying labels of training samples, because the transitional loss functions are equally applied to all the samples.
Jim Jing-Yan Wang +3 more
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Evolved-Cooperative Correntropy-Based Extreme Learning Machine for Robust Prediction
Entropy, 2019 In recent years, the correntropy instead of the mean squared error has been widely taken as a powerful tool for enhancing the robustness against noise and outliers by forming the local similarity measurements.
Wenjuan Mei +4 more
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Cyclic Correntropy: Foundations and Theories
IEEE Access, 2018 Over the past several decades, cyclostationarity has been regarded as one of the most significant theories in the research of non-stationary signal processing; therefore, it has been widely used to solve a large variety of scientific problems, such as ...
Tao Liu, Tianshuang Qiu, Shengyang Luan
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Maximum correntropy unscented filter [PDF]
International Journal of Systems Science, 2017 The unscented transformation (UT) is an efficient method to solve the state estimation problem for a non-linear dynamic system, utilizing a derivative-free higher-order approximation by approximating a Gaussian distribution rather than approximating a non-linear function.
Xi Liu 0006 +4 more
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Correntropy-Based Constructive One Hidden Layer Neural Network [PDF]
AlgorithmsOne of the main disadvantages of the traditional mean square error (MSE)-based constructive networks is their poor performance in the presence of non-Gaussian noises.
Mojtaba Nayyeri +5 more
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Entropy, 2020 The complex correntropy has been successfully applied to complex domain adaptive filtering, and the corresponding maximum complex correntropy criterion (MCCC) algorithm has been proved to be robust to non-Gaussian noises.
Fei Dong, Guobing Qian, Shiyuan Wang
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Remote Sensing, 2022 To improve the accuracy of the maximum correntropy Kalman filter (MCKF) in wireless sensors networks (WSNs) positioning, a dynamic self-tuning maximum correntropy Kalman filter (DSTMCKF) is proposed, where innovation and the sensors information of the ...
Tianrui Liao +4 more
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Online Gradient Descent for Kernel-Based Maximum Correntropy Criterion
Entropy, 2019 In the framework of statistical learning, we study the online gradient descent algorithm generated by the correntropy-induced losses in Reproducing kernel Hilbert spaces (RKHS).
Baobin Wang, Ting Hu
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