Oct 11, 2021 · In this paper, we propose a novel multi-view subspace clustering method with Kronecker-basis-representation-based tensor sparsity measure (MSC-KBR)

Nov 1, 2021 · In this paper, we propose a novel multi-view subspace clustering method with Kronecker-basis-representation-based tensor sparsity measure (MSC- ...

Abstract: Multi-view data are popular in many machine learning and computer vision applications. For example, in computer vision fields, one object can be ...

In this paper, we propose a novel multi-view subspace clustering method with Kronecker-basis-representation-based tensor sparsity measure (MSC-KBR) to address ...

Multi-view subspace clustering with Kronecker-basis-representation-based tensor sparsity measure ; Journal: Machine Vision and Applications, 2021, № 6 ; Publisher ...

Multi-view subspace clustering employs learned self-representation from multiple tensor decompositions to exploit the low-rank information.

Multi-view subspace clustering methods have employed learned self-representation tensors from different tensor decompositions to exploit low rank information.

In this paper, we address the multi-view subspace clustering problem. Our method utilizes the circulant algebra for tensor, which is constructed by stacking ...

Sep 8, 2024 · Specifically, in multi-view tensor clustering, we analyze the higher-order correlations among different modes of a self-representation tensor, ...

Multi-view subspace clustering with Kronecker-basis-representation-based tensor sparsity measure. Gui-Fu Lu, Hua Li, Yong Wang, Ganyi Tang. Machine Vision and ...