—Randomized testing is an effective method for testing software units. Thoroughness of randomized unit testing varies widely according to the settings of certain parameters, such...
Traditional tensor decompositions such as the CANDECOMP / PARAFAC (CP) and Tucker decompositions yield higher-order principal components that have been used to understand tensor d...
Abstract. Sparse signal models learned from data are widely used in audio, image, and video restoration. They have recently been generalized to discriminative image understanding t...
Julien Mairal, Marius Leordeanu, Francis Bach, Mar...
Local feature approaches to vision geometry and object recognition are based on selecting and matching sparse sets of visually salient image points, known as `keypoints' or `p...
Establishing point correspondences between images is a key step for 3D-shape computation. Nevertheless, shape extraction and point correspondence are treated, usually, as two diffe...