231 search results - page 10 / 47 » Spectral domain-transfer learning |
PAKDD
2004
ACM
14 years 1 months ago
2004
ACM
The use of unlabeled data to aid classification is important as labeled data is often available in limited quantity. Instead of utilizing training samples directly into semi-super...
KDD
2008
ACM
14 years 8 months ago
2008
ACM
Traditional spectral classification has been proved to be effective in dealing with both labeled and unlabeled data when these data are from the same domain. In many real world ap...
NIPS
2007
13 years 9 months ago
2007
Learning the common structure shared by a set of supervised tasks is an important practical and theoretical problem. Knowledge of this structure may lead to better generalization ...
ICML
2007
IEEE
14 years 9 months ago
2007
IEEE
Feature selection aims to reduce dimensionality for building comprehensible learning models with good generalization performance. Feature selection algorithms are largely studied ...
NIPS
2004
13 years 9 months ago
2004
We present an algorithm to perform blind, one-microphone speech separation. Our algorithm separates mixtures of speech without modeling individual speakers. Instead, we formulate ...