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...
In a seminal paper, Amari (1998) proved that learning can be made more efficient when one uses the intrinsic Riemannian structure of the algorithms' spaces of parameters to po...
: Directories provide a general mechanism for describing resources and enabling information sharing within and across organizations. Directories must resolve differing structures a...
The verification of large radio-frequency/millimeter-wave (RF/MM) integrated circuits (ICs) has regained attention for high-performance designs beyond 90nm and 60GHz. The traditio...
Abstract--This paper deals with the reconstruction of T1-T2 correlation spectra in nuclear magnetic resonance relaxometry. The ill-posed character and the large size of this invers...