Probabilistic data is coming as a new deluge along with the technical advances on geographical tracking, multimedia processing, sensor network and RFID. While similarity search is...
Sets of local features that are invariant to common image transformations are an effective representation to use when comparing images; current methods typically judge feature set...
With the advance of hardware and communication technologies, stream time series is gaining ever-increasing attention due to its importance in many applications such as financial da...
The success of tensor-based subspace learning depends heavily on reducing correlations along the column vectors of the mode-k flattened matrix. In this work, we study the problem ...
Shuicheng Yan, Dong Xu, Stephen Lin, Thomas S. Hua...
There are several pieces of information that can be utilized in order to improve the efficiency of similarity searches on high-dimensional data. The most commonly used information...