The C-loss function for pattern classification

DOI10.1016/j.patcog.2013.07.017zbMath1326.68253OpenAlexW2088622335MaRDI QIDQ898303

Jose C. Principe, Abhishek Singh, Rosha Pokharel

Publication date: 8 December 2015

Published in: Pattern Recognition (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.patcog.2013.07.017

zbMATH Keywords

classificationneural networkloss functionbackprojectioncorrentropy

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05) Pattern recognition, speech recognition (68T10)

Related Items (13)

CTSVM: a robust twin support vector machine with correntropy-induced loss function for binary classification problems ⋮ Kernel-based sparse regression with the correntropy-induced loss ⋮ A robust outlier control framework for classification designed with family of homotopy loss function ⋮ Joint learning adaptive metric and optimal classification hyperplane ⋮ A robust classification framework with mixture correntropy ⋮ Robust Support Vector Machines for Classification with Nonconvex and Smooth Losses ⋮ A Robust Regression Framework with Laplace Kernel-Induced Loss ⋮ Maximum correntropy adaptation approach for robust compressive sensing reconstruction ⋮ Quadratic Majorization for Nonconvex Loss with Applications to the Boosting Algorithm ⋮ Robust support vector machines based on the rescaled hinge loss function ⋮ Learning with correntropy-induced losses for regression with mixture of symmetric stable noise ⋮ Analysis of Regression Algorithms with Unbounded Sampling ⋮ Cauchy kernel-based maximum correntropy Kalman filter

Uses Software

• UCI-ml
• PRMLT

Cites Work

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• Information theoretic learning with adaptive kernels
• Heteroscedastic linear feature extraction based on sufficiency conditions
• Linear dimensionality reduction by maximizing the Chernoff distance in the transformed space
• The correntropy MACE filter
• Learning Deep Architectures for AI
• Correntropy: Properties and Applications in Non-Gaussian Signal Processing
• Generalized correlation function: definition, properties, and application to blind equalization
• On Estimation of a Probability Density Function and Mode
• Convexity, Classification, and Risk Bounds
• Multicategory ψ-Learning
• Soft margins for AdaBoost

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