减震 发表于 2025-3-25 05:44:49
,, Regularized Correntropy,Sparse signal representation arises in application of compressed sensing and has been considered as a significant technique in computer vision and machine learning . Based on the ..-.. equivalence theory , the solution of an ..-minimization problem is equal to that of an .. minimization problem under certain conditions.correspondent 发表于 2025-3-25 10:47:27
Ran He,Baogang Hu,Liang WangIncludes supplementary material:跳动 发表于 2025-3-25 13:21:41
Robust Recognition via Information Theoretic Learning978-3-319-07416-0Series ISSN 2191-5768 Series E-ISSN 2191-5776constitute 发表于 2025-3-25 16:55:42
Introduction,ived from the statistical definition of a breakdown point , is the ability of an algorithm that tolerates a large amount of outliers. Therefore, a robust method should be effective enough to reject outliers in images and perform classification only on uncorrupted pixels. In the past decadesartifice 发表于 2025-3-25 22:46:37
M-Estimators and Half-Quadratic Minimization,binations of order statistics), R-estimator (estimator based on rank transformation) , RM estimator (repeated median) , and LMS estimator (estimator using the least median of squares) . When information theoretic learning is applied to robust statistics, the Gaussian kernel in entropyPalpate 发表于 2025-3-26 03:14:58
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Correntropy and Linear Representation,samples are available. However, in practice, only a small number of samples are available for an object class. Hence linear representation methods are developed to generalize the representational capacity of available samples.