Pattern Recognition
Robust feature extraction via information theoretic learning
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Robust Discriminant Analysis Based on Nonparametric Maximum Entropy
ACML '09 Proceedings of the 1st Asian Conference on Machine Learning: Advances in Machine Learning
Using correntropy as a cost function in linear adaptive filters
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Correntropy based matched filtering for classification in sidescan sonar imagery
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
A test of independence based on a generalized correlation function
Signal Processing
The mee principle in data classification: A perceptron-based analysis
Neural Computation
WSEAS TRANSACTIONS on COMMUNICATIONS
Extraction of signals with specific temporal structure using kernel methods
IEEE Transactions on Signal Processing
Robust semi-supervised learning for biometrics
LSMS/ICSEE'10 Proceedings of the 2010 international conference on Life system modeling and and intelligent computing, and 2010 international conference on Intelligent computing for sustainable energy and environment: Part I
Label propagation algorithm based on non-negative sparse representation
LSMS/ICSEE'10 Proceedings of the 2010 international conference on Life system modeling and simulation and intelligent computing, and 2010 international conference on Intelligent computing for sustainable energy and environment: Part III
Correntropy function for fundamental frequency determination of musical instrument samples
Expert Systems with Applications: An International Journal
Correntropy based feature selection using binary projection
Pattern Recognition
A regularized correntropy framework for robust pattern recognition
Neural Computation
A performance and energy comparison of FPGAs, GPUs, and multicores for sliding-window applications
Proceedings of the ACM/SIGDA international symposium on Field Programmable Gate Arrays
Selective ensemble of support vector data descriptions for novelty detection
ISNN'12 Proceedings of the 9th international conference on Advances in Neural Networks - Volume Part I
Correntropy-Based document clustering via nonnegative matrix factorization
ICANN'12 Proceedings of the 22nd international conference on Artificial Neural Networks and Machine Learning - Volume Part II
Proceedings of the ACM/SIGDA international symposium on Field programmable gate arrays
Euler Principal Component Analysis
International Journal of Computer Vision
Linear discriminant analysis with maximum correntropy criterion
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part I
Adaptive kernel size selection for correntropy based metric
ACCV'12 Proceedings of the 11th international conference on Computer Vision - Volume Part I
Robust spectral regression for face recognition
Neurocomputing
Kernel minimum error entropy algorithm
Neurocomputing
The C-loss function for pattern classification
Pattern Recognition
Regularized discriminant entropy analysis
Pattern Recognition
| Hi-index | 35.69 |
The optimality of second-order statistics depends heavily on the assumption of Gaussianity. In this paper, we elucidate further the probabilistic and geometric meaning of the recently defined correntropy function as a localized similarity measure. A close relationship between correntropy and M-estimation is established. Connections and differences between correntropy and kernel methods are presented. As such correntropy has vastly different properties compared with second-order statistics that can be very useful in non-Gaussian signal processing, especially in the impulsive noise environment. Examples are presented to illustrate the technique.