A robust classification framework with mixture correntropy

DOI10.1016/j.ins.2019.04.016zbMath1454.62202OpenAlexW2939355031MaRDI QIDQ2214988

Liming Yang, Qiangqiang Ren, Yidan Wang

Publication date: 10 December 2020

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2019.04.016

zbMATH Keywords

robustnessFisher consistencysupport vector machinecorrentropyhalf quadratic optimization algorithm

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Statistical aspects of information-theoretic topics (62B10)

Related Items (3)

Outlier-robust Kalman filters with mixture correntropy ⋮ Joint learning adaptive metric and optimal classification hyperplane ⋮ Twin minimax probability machine for pattern classification

Uses Software

• SHOGUN
• UCI-ml

Cites Work

• Unnamed Item
• The C-loss function for pattern classification
• A note on margin-based loss functions in classification
• Support-vector networks
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• Correntropy: Properties and Applications in Non-Gaussian Signal Processing
• Generalized correlation function: definition, properties, and application to blind equalization
• Robust and Discriminative Labeling for Multi-Label Active Learning Based on Maximum Correntropy Criterion
• Generalized Correntropy for Robust<?Pub _newline ?>Adaptive Filtering
• Robust Multidimensional Scaling Using a Maximum Correntropy Criterion
• Robust Principal Component Analysis Based on Maximum Correntropy Criterion

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