Nov 4, 2016 · The traditional methods for solving MDS are susceptible to outliers. Here, a unified framework is proposed, where the MDS is treated as ...
By doing so, MDS can cope with an initial dissimilarity matrix contaminated with outliers, because the correntropy criterion is closely related to M-estimators.
Here, a unified framework is proposed, where the MDS is treated as maximization of a correntropy criterion, which is solved by half-quadratic optimization in a ...
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A unified framework where the MDS is treated as maximization of a correntropy criterion, which is solved by half-quadratic optimization in a multiplicative ...
Multidimensional scaling (MDS) refers to a class of dimensionality reduction techniques, which represent entities as points in a low-dimensional space so ...
tablished with the maximum correntropy criterion (MCC), which is related to the Welsch. M-estimator. By doing so, a unified framework emerges that extends ...
This paper considers an alternative approach, emphasizing data exploration and robustness to model misspecification. The strategy is applied to problems in ...
Robust multidimensional scaling using a maximum correntropy criterion. FD Mandanas, CL Kotropoulos. IEEE Transactions on Signal Processing 65 (4), 919-932, 2016.
Abstract—The maximum correntropy criterion (MCC) has re- cently been successfully applied in robust regression, classification.
Robust compressive sensing (CS) aims to recover the sparse signals from noisy measurements perturbed by non-Gaussian (i.e., heavy-tailed) noises, ...