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pro vyhledávání: '"Gu, Zecang"'
Unsupervised clustering algorithm can effectively reduce the dimension of high-dimensional unlabeled data, thus reducing the time and space complexity of data processing. However, the traditional clustering algorithm needs to set the upper bound of t
Externí odkaz:
http://arxiv.org/abs/2201.03449
In this paper we proposed an ultimate theory to solve the multi-target control problem through its introduction to the machine learning framework in automatic driving, which explored the implementation of excellent drivers' knowledge acquisition. Now
Externí odkaz:
http://arxiv.org/abs/1812.03007
Autor:
Gu, Zecang, Dong, Ling
For pattern recognition like image recognition, it has become clear that each machine-learning dictionary data actually became data in probability space belonging to Euclidean space. However, the distances in the Euclidean space and the distances in
Externí odkaz:
http://arxiv.org/abs/1801.01972
Publikováno v:
Computational Intelligence & Neuroscience. 4/9/2022, p1-7. 7p.