… of the kernel function, Kufi to the M-estimator loss function, ufi which is given by Kufi º
1 ¿ ufi. The function ufi is a redescending M-estimator and is nonnegative, symmetric, and …

… We introduce a robust estimator called generalized projection based M-estimator (gpbM)
which does not require the user to specify any scale parameters. For multiple inlier structures, …

… In the Monte Carlo study of Section 8 we include a one-step M-estimator of scoring type for
the logistic and Poisson regression models starting from a projection estimator. The simula…

… Furthermore, the modified algorithm is easily generalized to … Consequently, when comparing
M-estimator scores for different … Therefore, when comparing M-estimator scores at different …

… We propose a solution to the problem of robust subspace estimation using the projection
based M-estimator. … We will generalize the robust projection based M-estimator (pbM) of [3,13] …

… M-estimators [16]: M-estimator is a generalized maximum… the M-estimator as a
projection-based optimization problem, … We compare the proposed methods with Tukey M-estimator, …

… This paper introduces a high breakdown M-estimator (called HBM for short) with a
differentiable cost function that can be directly optimized by iteratively reweighted least squares …

… In contrast, if we consider a constrained M-estimator and … If we consider a constrained
M-estimator, setting the value of … universal projection-based estimator for regression in …

… Among them, M-estimator and least median of squares (LMedS) are imported from statistics.
… The advantage of such reinterpretation is that the scale of M-estimator is replaced by the …

… One of this cost function is already widely used in the forms of the Hough transform and
generalised projection based M-estimator, and it is interpreted as a conditional density function …