Outlier-Robust PCA: The High-Dimensional Case
نویسندگان
چکیده
منابع مشابه
Robust PCA for High-Dimensional Data
We consider the dimensionality-reduction problem for a contaminated data set in a very high dimensional space, i.e., the problem of finding a subspace approximation of observed data, where the number of observations is of the same magnitude as the number of variables of each observation, and the data set contains some outlying observations. We propose a High-dimension Robust Principal Component...
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ژورنال
عنوان ژورنال: IEEE Transactions on Information Theory
سال: 2013
ISSN: 0018-9448,1557-9654
DOI: 10.1109/tit.2012.2212415