221 search results - page 4 / 45 » Learning from Labeled and Unlabeled Data Using Random Walks |
MIR
2005
ACM
14 years 1 months ago
2005
ACM
In this paper, we propose a transductive learning method for content-based image retrieval: Multiple Random Walk (MRW). Its basic idea is to construct two generative models by mea...
IJCNLP
2004
Springer
14 years 1 months ago
2004
Springer
Multi-document discourse analysis has emerged with the potential of improving various NLP applications. Based on the newly proposed Cross-document Structure Theory (CST), this pap...
IJCAI
2003
13 years 9 months ago
2003
In traditional text classification, a classifier is built using labeled training documents of every class. This paper studies a different problem. Given a set P of documents of a ...
ICML
2002
IEEE
14 years 8 months ago
2002
IEEE
Supervised learning techniques for text classi cation often require a large number of labeled examples to learn accurately. One way to reduce the amountoflabeled datarequired is t...
ICASSP
2011
IEEE
12 years 11 months ago
2011
IEEE
Current hidden Markov acoustic modeling for large vocabulary continuous speech recognition (LVCSR) relies on the availability of abundant labeled transcriptions. Given that speech...