青云翻译

Low-dimensional manifold structure by learning the data set, lead to local adaptive to maintain the nuclear manifold distance-ad-kmd concept, consider the local neighborhood of data points, but also a global grasp of the data set as a whole structure, making the algorithm capable of complex distribu

By studying the data in this article sets the structure of low-dimensional manifolds, leads to local Adaptive maintaining "nuclear manifold distance" concept of-ad-KMD, taking into account both the local neighborhood information data points, and global, grasp the overall structure of the data set, d

This article through the study data set low Manifold structure, draws out the partial auto-adapted maintenance “the nuclear manifold distance” - the ad-KMD concept, both has considered the data point partial neighborhood information, and the overall situation grasps the data set the overall construc

Through this study data set of the low-dimensional-CLASS-structure, and leads the local Adaptive keep the core stream-distance" - an AD-KMD concept, taking into account both the data points of the local neighborhood information, and global data sets to grasp the whole structure, so that algorithms c

By studying the data in this article sets the structure of low-dimensional manifolds, leads to local Adaptive maintaining "nuclear manifold distance" concept of-ad-KMD, taking into account both the local neighborhood information data points, and global, grasp the overall structure of the data set, d