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...
This paper explores probabilistic lexico-syntactic pattern matching, also known as soft pattern matching. While previous methods in soft pattern matching are ad hoc in computing t...
Abstract. This paper presents a novel framework for detecting abnormal pedestrian and vehicle behaviour by modelling cross-correlation among different co-occurring objects both loc...
This paper explores a novel application of queuing theory to the corrective software maintenance problem to support quantitative balancing between resources and responsiveness. In...