Sciweavers

2512 search results - page 52 / 503
» Learning from Highly Structured Data by Decomposition
Sort
View
ICDM
2003
IEEE
104views Data Mining» more  ICDM 2003»
15 years 3 months ago
Structure Search and Stability Enhancement of Bayesian Networks
Learning Bayesian network structure from large-scale data sets, without any expertspecified ordering of variables, remains a difficult problem. We propose systematic improvements ...
Hanchuan Peng, Chris H. Q. Ding
CVPR
2010
IEEE
14 years 7 months ago
P-N learning: Bootstrapping binary classifiers by structural constraints
This paper shows that the performance of a binary classifier can be significantly improved by the processing of structured unlabeled data, i.e. data are structured if knowing the ...
Zdenek Kalal, Jiri Matas, Krystian Mikolajczyk
ICIP
2005
IEEE
15 years 11 months ago
Color signal decomposition method using 3-D Gamut boundary of multi-primary display
Color signal decomposition method is to decompose the conventional three-primary colors(RGB) into the multiprimary control values of multi-primary display(MPD) under the constraint...
Dong-Woo Kang, Yang-Ho Cho, Myong-Young Lee, Tae-Y...
KDD
2010
ACM
274views Data Mining» more  KDD 2010»
15 years 1 months ago
Grafting-light: fast, incremental feature selection and structure learning of Markov random fields
Feature selection is an important task in order to achieve better generalizability in high dimensional learning, and structure learning of Markov random fields (MRFs) can automat...
Jun Zhu, Ni Lao, Eric P. Xing
ICML
2002
IEEE
15 years 10 months ago
Kernels for Semi-Structured Data
Semi-structured data such as XML and HTML is attracting considerable attention. It is important to develop various kinds of data mining techniques that can handle semistructured d...
Hisashi Kashima, Teruo Koyanagi