Outlier removal - Open Access .click

Numerical Algorithms, 2017
The authors develop a method for removing outliers using quasi-interpolation. The authors use quasi-interpolation and the approximation error of a function to create a boundary beyond which a data point is adjudicated as an outlier and removed from the dataset.
Anat Amir, David Levin
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Gamma Mixture Models for Outlier Removal

2018 25th IEEE International Conference on Image Processing (ICIP), 2018
In this paper, we introduce a probabilistic outlier model which is seamlessly integrated into machine learning frameworks (e.g., boosting and deep neural network) to accurately identify outliers in training samples. With two Gamma mixtures, the proposed model can estimate the distribution of inlier and outlier samples respectively and generates their ...
Xin Wu, Ling Cai 0003, Rongrong Ji
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Optimal outlier removal in high-dimensional

Proceedings of the thirty-third annual ACM symposium on Theory of computing, 2001
We study the problem of finding an outlier-free subset of a set of points (or a probability distribution) in n-dimensional Euclidean space. A point x is defined to be a β-outlier if there exists some direction w in which its squared distance from the mean along w is greater than β times the average squared distance from the mean along w [1].
John Dunagan, Santosh S. Vempala
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outlier detection
outliers
fos: computer and information sciences

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