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- Liangli Zhen, Xi Peng, Dezhong Peng
- JSW
- 2013

- Liangli Zhen, Dezhong Peng, Zhang Yi, Yong Xiang, Peng Chen
- IEEE transactions on neural networks and learning…
- 2016

In an underdetermined mixture system with n unknown sources, it is a challenging task to separate these sources from their m observed mixture signals, where . By exploiting the technique of sparse coding, we propose an effective approach to discover some 1-D subspaces from the set consisting of all the time-frequency (TF) representation vectors of observed… (More)

- Liangli Zhen, Zhang Yi, Xi Peng, Dezhong Peng
- 2013

It is a key to construct a similarity graph in graph-oriented subspace learning and clustering. In a similarity graph, each vertex denotes a data point and the edge weight represents the similarity between two points. There are two popular schemes to construct a similarity graph, i.e., pairwise distance based scheme and linear representation based scheme.… (More)

- Miqing Li, Liangli Zhen, Xinsheng Yao
- IEEE Computational Intelligence Magazine
- 2017

Rapid development of evolutionary algor ithms in handling many-objective optimization problems requires viable methods of visualizing a high-dimensional solution set. The parallel coordinates plot which scales well to high-dimensional data is such a method, and has been frequently used in evolutionary many-objective optimization. However, the parallel… (More)

- Liangli Zhen, Dezhong Peng, Xinsheng Yao
- ArXiv
- 2017

Subspace clustering aims to group data points into multiple clusters of which each corresponds to one subspace. Most existing subspace clustering methods assume that the data could be linearly represented with each other in the input space. In practice, however, this assumption is hard to be satisfied. To achieve nonlinear subspace clustering, we propose a… (More)

- Liangli Zhen, Miqing Li, Ran Cheng, Dezhong Peng, Xinsheng Yao
- SEAL
- 2017

- Liangli Zhen, Zhang Yi, Xi Peng, Dezhong Peng
- ArXiv
- 2013

It is a key to construct a similarity graph in graph-oriented subspace learning and clustering. In a similarity graph, each vertex denotes a data point and the edge weight represents the similarity between two points. There are two popular schemes to construct a similarity graph, i.e., pairwise distance based scheme and linear representation based scheme.… (More)

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