Many computer vision and pattern recognition algorithms are very sensitive to the choice of an appropriate distance metric. Some recent research sought to address a variant of the...
The performance of many supervised and unsupervised learning algorithms is very sensitive to the choice of an appropriate distance metric. Previous work in metric learning and ada...
We define a novel metric on the space of closed planar curves which decomposes into three intuitive components. According to this metric centroid translations, scale changes and ...
Ganesh Sundaramoorthi, Andrea Mennucci, Stefano So...
—Application level traffic classification is one of the major issues in network monitoring and traffic engineering. In our previous study, we proposed a new traffic classificatio...
Jae Yoon Chung, Byungchul Park, Young J. Won, John...
In this paper, we propose a novel metric learning method based on regularized moving least squares. Unlike most previous metric learning methods which learn a global Mahalanobis d...