Feature selection is an important task in effective data mining. A new challenge to feature selection is the so-called “small labeled-sample problem” in which labeled data is...
This paper explores a recently proposed and rarely reported subspace learning method, Spectral Regression Discriminant Analysis (SRDA) [1, 2], on silhouette based human action rec...
We show a variety of ways to cluster student activity datasets using different clustering and subspace clustering algorithms. Our results suggest that each algorithm has its own st...
—This paper proposes a feature extraction method for motor imagery brain–computer interface (BCI) using electroencephalogram. We consider the primary neurophysiologic phenomeno...
Haihong Zhang, Zhang Yang Chin, Kai Keng Ang, Cunt...
Motivated by the principle of agnostic learning, we present an extension of the model introduced by Balcan, Blum, and Gupta [3] on computing low-error clusterings. The extended mod...