Abstract: Outlier detection is to separate anomalous data from inliers in the dataset. Recently, the most deep learning methods of outlier detection leverage an auxiliary reconstruction task by ...
Abstract: We present a novel solution to the problem of subspace outlier detection that does not assume prior knowledge of the number of outliers nor the dimension of the inliers subspace. The ...