Speaker：Wen Li (South China Normal University)

Time：2023-5-24, 9:30

Location：Conference Room 686 at the 6th floor of Shuli Building at Haiyun Campus

Abstract:

By utilizing the low rank nature of big data, the tensor SVD decomposition and the MCP function, a non convex multi-view subspace clustering tensor low rank minimization model based on learning expression tensor and affinity matrix is established. An algorithm based on the ADMM framework was proposed, and the convergence and parameter sensitivity of the algorithm were discussed. The clustering performance of the proposed method in terms of scene and face datasets shows that it is more effective than the existing methods.