This paper proposes a novel subspace approach towards direct identification of a residual model for fault detection and isolation (FDI) in a system with non-uniformly sampled mult...
In this paper, we study the problem of discovering interesting patterns through user's interactive feedback. We assume a set of candidate patterns (i.e., frequent patterns) h...
Searching and extracting meaningful information out of highly heterogeneous datasets is a hot topic that received a lot of attention. However, the existing solutions are based on e...
The number of mentally ill people is increasing globally each year. Despite major medical advances, the identification of genetic and environmental factors responsible for mental ...
Abstract. Clustering high dimensional data with sparse features is challenging because pairwise distances between data items are not informative in high dimensional space. To addre...