With the rapid advances in digital imaging and communication technologies, recently image
set classification has attracted significant attention and has been widely used in many real …

By characterizing each image set as a nonsingular covariance matrix on the symmetric
positive definite (SPD) manifold, the approaches of visual content classification with image …

Clustering of multi-view data has attracted great interest in machine learning. Multi-view data
is based on complementary and consistent information due to the collection of numerous …

Modeling image sets as points on Grassmann manifold has attracted increasing interests in
computer vision community and has been applied to many applications. However, such …

Multichannel electroencephalogram (EEG) signals, which directly reflects the brain's inner
workings state, is an powerful tool to diagnosis depression. For EEG-based depression …

Tensor-oriented multi-view subspace clustering has achieved significant strides in
assessing high-order correlations of multi-view data. Nevertheless, most of existing …

Maintaining a normal sintering condition is vital to ensuring the quality of nonferrous metals
in a rotary kiln. Identification of the sintering conditions is a crucial component of a condition …

In the era of information explosion, clustering analysis of multi-view data plays a crucial role
in revealing the intrinsic structures of data. Despite the advancements in existing multi-view …

Clustering has received a lot of attention and research in many important fields, such as
machine learning and data mining. Especially, the clustering method based on non-negative …

Abstract Concept factorization (CF) is a powerful tool in subspace learning. Recently graph-
based CF and local coordinate CF have been proposed to exploit the intrinsic geometrical …