The use of compression algorithms in machine learning tasks such as clustering and classification has appeared in a variety of fields, sometimes with the promise of reducing probl...
This paper studies the problem of learning a full range of pairwise affinities gained by integrating local grouping cues for spectral segmentation. The overall quality of the spect...
Tae Hoon Kim (Seoul National University), Kyoung M...
A metascalable (or “design once, scale on new architectures”) parallel computing framework has been developed for large spatiotemporal-scale atomistic simulations of materials...
Ken-ichi Nomura, Richard Seymour, Weiqiang Wang, H...
We present a junction tree decomposition based algorithm for parallel exact inference. This is a novel parallel exact inference method for evidence propagation in an arbitrary jun...
This paper presents a novel motion segmentation algorithm on the basis of mixture of Dirichlet process (MDP) models, a kind of nonparametric Bayesian framework. In contrast to pre...