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» On the Optimality of the Dimensionality Reduction Method
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PKDD
2009
Springer
153views Data Mining» more  PKDD 2009»
16 years 25 days ago
Subspace Regularization: A New Semi-supervised Learning Method
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, ...
Yan-Ming Zhang, Xinwen Hou, Shiming Xiang, Cheng-L...
CVPR
2008
IEEE
16 years 8 months ago
Robust tensor factorization using R1 norm
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...
Heng Huang, Chris H. Q. Ding
ICS
1995
Tsinghua U.
15 years 9 months ago
Run-Time Methods for Parallelizing Partially Parallel Loops
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...
PATMOS
2007
Springer
16 years 12 days ago
Soft Error-Aware Power Optimization Using Gate Sizing
—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...
ICML
2006
IEEE
16 years 7 months ago
Robust Euclidean embedding
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...
Lawrence Cayton, Sanjoy Dasgupta