Most existing semi-supervised learning methods are based on the smoothness assumption that data points in the same high density region should have the same label. This assumption, ...
Over the years, many tensor based algorithms, e.g. two dimensional principle component analysis (2DPCA), two dimensional singular value decomposition (2DSVD), high order SVD, have...
In this paper we give a new run–time technique for finding an optimal parallel execution schedule for a partially parallel loop, i.e., a loop whose parallelization requires syn...
Lawrence Rauchwerger, Nancy M. Amato, David A. Pad...
—Power consumption has emerged as the premier and most constraining aspect in modern microprocessor and application-specific designs. Gate sizing has been shown to be one of the...
Foad Dabiri, Ani Nahapetian, Miodrag Potkonjak, Ma...
We derive a robust Euclidean embedding procedure based on semidefinite programming that may be used in place of the popular classical multidimensional scaling (cMDS) algorithm. We...