548 search results - page 34 / 110 » Iterated importance sampling in missing data problems |
FUIN
2010
14 years 5 months ago
2010
Machine learning methods are often used to classify objects described by hundreds of attributes; in many applications of this kind a great fraction of attributes may be totally irr...
ICCV
2007
IEEE
16 years 26 days ago
2007
IEEE
Learning-based superresolution (SR) are popular SR techniques that use application dependent priors to infer the missing details in low resolution images (LRIs). However, their pe...
122
Voted
SIAMJO
2010
14 years 9 months ago
2010
This paper introduces a novel algorithm to approximate the matrix with minimum nuclear norm among all matrices obeying a set of convex constraints. This problem may be understood a...
IJHPCA
2010
14 years 9 months ago
2010
Sparse matrix operations achieve only small fractions of peak CPU speeds because of the use of specialized, indexbased matrix representations, which degrade cache utilization by i...
90
Voted
KDD
2009
ACM
15 years 11 months ago
2009
ACM
Stability is an important yet under-addressed issue in feature selection from high-dimensional and small sample data. In this paper, we show that stability of feature selection ha...