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 develops an algorithm to detect abnormalities of small animals' transplanted hearts in MRI, at early stage of rejection when the hearts do not display prominent ab...
In modern circuit design, it is difficult to provide reliable parametric yield prediction since the real distribution of process data is hard to measure. Most existing approaches ...
Markov networks are a common class of graphical models used in machine learning. Such models use an undirected graph to capture dependency information among random variables in a ...
The relationship between support vector machines (SVMs) and Takagi–Sugeno–Kang (TSK) fuzzy systems is shown. An exact representation of SVMs as TSK fuzzy systems is given for ...
Juan Luis Castro, L. D. Flores-Hidalgo, Carlos Jav...