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Many real-world problems involve multi-view high-dimension-small-sample-size data analysis, such as multi-omics data. The combination of multi-view databases is supposed to provide a better biological significance. However, the multi-view data always contain noise and outlying entries that result in inaccurate and unreliable. It has become an urgent need how to effectively analyze these data. We proposed...
In molecular biology, the selection of feature genes and tumor clustering are the hotspots and difficulties in bioinformatics research. The traditional PCA method based on the minimization of the squares of the loss function is sensitive to the outliers and noise. Therefore, it is necessary to design a new method to weaken the effects of errors and noise. In this paper, we propose a novel PCA method...
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