We address an approximation method for Gaussian process (GP) regression, where we approximate covariance by a block matrix such that diagonal blocks are calculated exactly while o...
Root lattices are efficient sampling lattices for reconstructing isotropic signals in arbitrary dimensions, due to their highly symmetric structure. One root lattice, the Cartesia...
Subspace clustering and feature extraction are two of the most commonly used unsupervised learning techniques in computer vision and pattern recognition. State-of-theart technique...
Risheng Liu, Zhouchen Lin, Fernando De la Torre, Z...
—Graph visualization has been widely used to understand and present both global structural and local adjacency information in relational datasets (e.g., transportation networks, ...
Image parsing remains difficult due to the need to combine
local and contextual information when labeling a
scene. We approach this problem by using the epitome as a
prior over ...
Jonathan Warrell, Simon J. D. Prince, Alastair P. ...