377 search results - page 38 / 76 » Learning Linear Ordering Problems for Better Translation |
JMLR
2010
14 years 4 months ago
2010
We use convex relaxation techniques to provide a sequence of regularized low-rank solutions for large-scale matrix completion problems. Using the nuclear norm as a regularizer, we...
ICDM
2003
IEEE
15 years 3 months ago
2003
IEEE
Learning Bayesian network structure from large-scale data sets, without any expertspecified ordering of variables, remains a difficult problem. We propose systematic improvements ...
ICML
2004
IEEE
15 years 10 months ago
2004
IEEE
Conditional Random Fields (CRFs; Lafferty, McCallum, & Pereira, 2001) provide a flexible and powerful model for learning to assign labels to elements of sequences in such appl...
103
click to vote
ICPR
2008
IEEE
15 years 11 months ago
2008
IEEE
Recognizing and localizing objects is a classical problem in computer vision that is an important stage for many automated systems. In order to perform object recognition many res...
PRL
2011
14 years 4 months ago
2011
In some real world applications, such as spectrometry, functional models achieve better predictive performances if they work on the derivatives of order m of their inputs rather t...