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Correntropy with Nonnegative Constraint
2014Nonnegativity constraint is more consistent with the biological modeling of visual data and often leads to better performance for data representation and graph learning [66]. In this chapter, we present an overview of some recent advances in correntropy with nonnegative constraint.
Ran He +3 more
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A correntropy function based on coincidence detection
Pattern Recognition Letters, 2017Abstract This work presents a new generalized correlation function (correntropy) estimator based on collision entropy. Both the proposed approach and the standard correntropy estimator, published in 2006, can be regarded as coincidence counting methods, one using soft coincidence detection, whereas ours detects hard coincidences.
Jugurta Montalvão +2 more
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Orthogonal Maximum Correntropy Learning
2022 IEEE 32nd International Workshop on Machine Learning for Signal Processing (MLSP), 2022Mingfei Lu, Badong Chen
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Correntropy and Linear Representation
2014The nearest neighbor (NN) classifier is the most popular method for image-based object recognition. In NN classifier, the representational capacity of an image database and the recognition rate depend on how registered samples are selected to represent object’s possible variations and also how many samples are available.
Ran He +3 more
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Correntropy in Data Classification
2012In this chapter, the usability of the correntropy-based similarity measure in the paradigm of statistical data classification is addressed. The basic theme of the chapter is to compare the performance of the correntropic loss function with the conventional quadratic loss function.
Mujahid N. Syed +2 more
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Correntropy based filtering for supernova detection
2016 International Joint Conference on Neural Networks (IJCNN), 2016The recent surge of huge astronomical telescopes opens new possibilities for astrophysical studies, with corresponding challenges regarding massive data analysis. Taking advantage of these new technologies, the High Cadence Transient Survey (HiTS) has developed a pipeline to detect transient astronomical phenomena, such as supernovae, by analyzing ...
Pablo Huentelemu +2 more
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Sequential Maximum Correntropy Kalman Filtering
Asian Journal of Control, 2018AbstractThis paper explores a linear state estimation problem in non‐Gaussian setting and suggests a computationally simple estimator based on the maximum correntropy criterion Kalman filter (MCC‐KF). The first MCC‐KF method was developed in Joseph stabilized form. It requires two n × n and one m × m matrix inversions, where n is a dimension of unknown
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Mixture Complex Correntropy for Adaptive Filter
IEEE Transactions on Circuits and Systems II: Express Briefs, 2019With the development of adaptive filtering theory and its application, the research on complex domain has attracted more attention. As a measure of local similarity, complex correntropy has been applied to adaptive filtering in the complex domain. The choice of kernel function plays a very important role in the performance of corresponding algorithms ...
Guobing Qian, Xiaohan Ning, Shiyuan Wang
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Correntropy based self-organizing map
2016 International Conference on Machine Learning and Cybernetics (ICMLC), 2016Self-organizing map (SOM) is regarded as a type of feedfoward neural network. It has been successfully used for unsupervised learning. However, the objective function of the traditional SOM relies on the mean squared error (MSE) criterion, which makes the performance of SOM become poor in the presence of noise.
Qing-Zhen Shang, Hong-Jie Xing
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Temporal Local Correntropy Representation for Fault Diagnosis of Machines
IEEE Transactions on Industrial Informatics, 2023Zhixi Feng, Shuyuan Yang
exaly