no code implementations • 3 Mar 2024 • Haiquan Zhao, Xuwu Wang, Shisong Chen, Zhixu Li, Xin Zheng, Yanghua Xiao
In this paper, we propose a task called Online Video Entity Linking OVEL, aiming to establish connections between mentions in online videos and a knowledge base with high accuracy and timeliness.
no code implementations • 18 Sep 2023 • Boyu Tian, Haiquan Zhao
By adding the correntropy to the error entropy, the proposed algorithm further enhances the ability of suppressing impulse noise and outliers.
no code implementations • 9 Sep 2023 • Haiquan Zhao, Yuan Gao, Yingying Zhu
In this paper, a generalized minimum error with fiducial points criterion (GMEEF) is presented by adopting the Generalized Gaussian Density (GGD) function as kernel.
no code implementations • 10 Apr 2023 • Dongxu Liu, Haiquan Zhao, Yang Zhou
Limited by fixed step-size and sparsity penalty factor, the conventional sparsity-aware normalized subband adaptive filtering (NSAF) type algorithms suffer from trade-off requirements of high filtering accurateness and quicker convergence behavior for sparse system identification.
no code implementations • 7 Nov 2022 • Haiquan Zhao, Zian Cao, Yida Chen
In addition, this paper also conducts a detailed theoretical performance analysis of the TLMM-NSAF algorithm and obtains the stable step size range and theoretical steady-state mean squared deviation (MSD) of the algorithm.
no code implementations • 20 Oct 2022 • Wenjing Xu, Haiquan Zhao, Shaohui Lv
However, its performance is mainly limited by two aspects, i. e, the correlated input signal and impulsive noise interference.
no code implementations • 23 Mar 2017 • Badong Chen, Lei Xing, Haiquan Zhao, Bin Xu, Jose C. Principe
The maximum correntropy criterion (MCC) has recently been successfully applied in robust regression, classification and adaptive filtering, where the correntropy is maximized instead of minimizing the well-known mean square error (MSE) to improve the robustness with respect to outliers (or impulsive noises).
no code implementations • 1 Aug 2016 • Badong Chen, Lei Xing, Bin Xu, Haiquan Zhao, Nanning Zheng, Jose C. Principe
Nonlinear similarity measures defined in kernel space, such as correntropy, can extract higher-order statistics of data and offer potentially significant performance improvement over their linear counterparts especially in non-Gaussian signal processing and machine learning.
no code implementations • 15 Sep 2015 • Badong Chen, Xi Liu, Haiquan Zhao, José C. Príncipe
Traditional Kalman filter (KF) is derived under the well-known minimum mean square error (MMSE) criterion, which is optimal under Gaussian assumption.
no code implementations • 8 Aug 2015 • Wentao Ma, Badong Chen, Jiandong Duan, Haiquan Zhao
Robust diffusion adaptive estimation algorithms based on the maximum correntropy criterion (MCC), including adaptation to combination MCC and combination to adaptation MCC, are developed to deal with the distributed estimation over network in impulsive (long-tailed) noise environments.
no code implementations • 12 Apr 2015 • Badong Chen, Lei Xing, Haiquan Zhao, Nanning Zheng, José C. Príncipe
In this work, we propose a generalized correntropy that adopts the generalized Gaussian density (GGD) function as the kernel (not necessarily a Mercer kernel), and present some important properties.