In this paper, we present a new algorithm for tracking the generalized signal subspace recursively. It is based on an interpretation of the generalized signal subspace as the solu...
Since the appearance changes of the target jeopardize visual measurements and often lead to tracking failure in practice, trackers need to be adaptive to non-stationary appearance...
Subspace learning approaches have attracted much attention in academia recently. However, the classical batch algorithms no longer satisfy the applications on streaming data or la...
Jun Yan, Benyu Zhang, Shuicheng Yan, Qiang Yang, H...
Document clustering has long been an important problem in information retrieval. In this paper, we present a new clustering algorithm ASI1, which uses explicitly modeling of the s...
Abstract. We formulate the problem of least squares temporal difference learning (LSTD) in the framework of least squares SVM (LS-SVM). To cope with the large amount (and possible ...