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In this brief, a novel method that constructs a sparse kernel machine is proposed. The proposed method generates attractors as sparse solutions from a built-in kernel machine via a dynamical system framework. By readjusting the corresponding coefficients and bias terms, a sparse kernel machine that approximates a conventional kernel machine is constructed.(More)
We deal with the nonlinear manifold learning problem to find a low-dimensional structure in high-dimensional data. Based on Gaussian random fields framework, we propose an approximate sampling method for coordinates on the manifolds. Experimentally the mean of samples are shown to be almost equal to the coordinates obtained by locally linear embedding where(More)
Retinal vessel segmentation is an indispensable step for automatic detection of retinal diseases with fundoscopic images. Though many approaches have been proposed, existing methods tend to miss fine vessels or allow false positives at terminal branches. Let alone undersegmentation, over-segmentation is also problematic when quantitative studies need to(More)
BACKGROUND The jugular vein cutdown for a totally implantable central venous port (TICVP) has 2 disadvantages: 2 separate incisions are needed and the risk for multiple vein occlusions. We sought to evaluate the feasibility of a cephalic vein (CV) cutdown in children. METHODS We prospectively followed patients who underwent a venous cutdown for(More)
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