We consider the problem of how to improve the efficiency of Multiple Kernel Learning (MKL). In literature, MKL is often solved by an alternating approach: (1) the minimization of ...
Zenglin Xu, Rong Jin, Haiqin Yang, Irwin King, Mic...
We present a pose estimation method for rigid
objects from single range images. Using 3D models of the
objects, many pose hypotheses are compared in a data-parallel
version of t...
In Kyu Park, Marcel Germann, Michael D. Breitenste...
We present a novel framework based on hidden Markov models (HMMs) for matching feature point sets, which capture the shapes of object contours of interest. Point matching algorith...
Basic data flow patterns which we call idioms, such as stream, transpose, reduction, random access and stencil, are common in scientific numerical applications. We hypothesize tha...
Jiahua He, Allan Snavely, Rob F. Van der Wijngaart...
Learning function relations or understanding structures of data lying in manifolds embedded in huge dimensional Euclidean spaces is an important topic in learning theory. In this ...