Results 131 to 140 of about 1,489 (178)
Some of the next articles are maybe not open access.
Maximum Correntropy Criterion-Based Hierarchical One-Class Classification
IEEE Transactions on Neural Networks and Learning Systems, 2021Due to the effectiveness of anomaly/outlier detection, one-class algorithms have been extensively studied in the past. The representatives include the shallow-structure methods and deep networks, such as the one-class support vector machine (OC-SVM), one-class extreme learning machine (OC-ELM), deep support vector data description (Deep SVDD), and ...
Jiuwen Cao +5 more
openaire +2 more sources
Maximum correntropy criterion partial least squares
Optik, 2018Abstract Partial least squares (PLS) has been extensively used to solve problems such as infrared quantitative analysis, economic data analysis, object tracking. PLS finds a linear regression model by projecting the predicted variables and the response to a new space.
Yi Mou +4 more
openaire +1 more source
A Privacy-Preserving Semisupervised Algorithm Under Maximum Correntropy Criterion
IEEE Transactions on Neural Networks and Learning Systems, 2022Existing semisupervised learning approaches generally focus on the single-agent (centralized) setting, and hence, there is the risk of privacy leakage during joint data processing. At the same time, using the mean square error criterion in such approaches does not allow one to efficiently deal with problems involving non-Gaussian distribution. Thus, in
Ling Zuo +3 more
openaire +2 more sources
Maximum Correntropy Criterion Constrained Kalman Filter
Volume 2: Mechatronics; Estimation and Identification; Uncertain Systems and Robustness; Path Planning and Motion Control; Tracking Control Systems; Multi-Agent and Networked Systems; Manufacturing; Intelligent Transportation and Vehicles; Sensors and Actuators; Diagnostics and Detection; Unmanned, Ground and Surface Robotics; Motion and Vibration Control Applications, 2017Non-Gaussian noise may degrade the performance of the Kalman filter because the Kalman filter uses only second-order statistical information, so it is not optimal in non-Gaussian noise environments. Also, many systems include equality or inequality state constraints that are not directly included in the system model, and thus are not incorporated in ...
Seyed Fakoorian +4 more
openaire +1 more source
Extended Information Filter under Maximum Correntropy Criterion
2020 35th Youth Academic Annual Conference of Chinese Association of Automation (YAC), 2020This study concerns the information filtering problem for nonlinear non-Gaussian systems. Under the maximum correntropy criterion (MCC), in the information filter framework, a novel information filter named maximum correntropy extended information filter (MCEIF) is proposed for nonlinear non-Gaussian systems.
Yuxin Feng +3 more
openaire +1 more source
Random Fourier Filters Under Maximum Correntropy Criterion
IEEE Transactions on Circuits and Systems I: Regular Papers, 2018Random Fourier adaptive filters (RFAFs) project the original data into a high-dimensional random Fourier feature space (RFFS) such that the network structure of filters is fixed while achieving similar performance with kernel adaptive filters. The commonly used error criterion in RFAFs is the well-known minimum mean-square error (MMSE) criterion, which
Shiyuan Wang +5 more
openaire +1 more source
Robust tensor factorization using maximum correntropy criterion
2016 23rd International Conference on Pattern Recognition (ICPR), 2016Traditional tensor decomposition methods, e.g., two dimensional principle component analysis (2DPCA) and two dimensional singular value decomposition (2DSVD), minimize mean square errors (MSE) and are sensitive to outliers. In this paper, we propose a new robust tensor factorization method using maximum correntropy criterion (MCC) to improve the ...
null Miaohua Zhang +4 more
openaire +1 more source
Extended Kalman filter under maximum correntropy criterion
2016 International Joint Conference on Neural Networks (IJCNN), 2016As a nonlinear extension of Kalman filter, the extended Kalman filter (EKF) is also based on the minimum mean square error (MMSE) criterion. In general, the EKF performs well in Gaussian noises. But its performance may deteriorate substantially when the system is disturbed by heavy-tailed impulsive noises.
Xi Liu, Hua Qu, Jihong Zhao, Badong Chen
openaire +1 more source
Maximum correntropy criterion for discriminative dictionary learning
2013 IEEE International Conference on Image Processing, 2013In this paper, a novel discriminative dictionary learning with pairwise constraints by maximum correntropy criterion is proposed for pair matching problem. Comparing with the conventional dictionary learning approaches, the proposed method has several advantages: (i) It can deal with the outliers and noises problem more efficiently during the ...
Pengyi Hao, Sei-ichiro Kamata
openaire +1 more source
Robust Principal Component Analysis Based on Maximum Correntropy Criterion
IEEE Transactions on Image Processing, 2011Principal component analysis (PCA) minimizes the mean square error (MSE) and is sensitive to outliers. In this paper, we present a new rotational-invariant PCA based on maximum correntropy criterion (MCC). A half-quadratic optimization algorithm is adopted to compute the correntropy objective.
Ran, He +3 more
openaire +2 more sources