Cited By
View all- Sheehy DCzumaj A(2018)Fréchet-stable signatures using persistence homologyProceedings of the Twenty-Ninth Annual ACM-SIAM Symposium on Discrete Algorithms10.5555/3174304.3175341(1100-1108)Online publication date: 7-Jan-2018
Recently, manifold learning has been widely exploited in pattern recognition, data analysis, and machine learning. This paper presents a novel framework, called Riemannian manifold learning (RML), based on the assumption that the input high-dimensional ...
Several algorithms have been proposed to analysis the structure of high-dimensional data based on the notion of manifold learning. They have been used to extract the intrinsic characteristic of different type of high-dimensional data by performing ...
Compressive sensing (CS) provides a new perspective for data reduction without compromising performance when the signal of interest is sparse or has intrinsically low-dimensional structure. The theoretical foundation for most of the existing studies on CS ...
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