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» A supervised learning approach for imbalanced data sets
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ACL
2006
13 years 10 months ago
Boosting Statistical Word Alignment Using Labeled and Unlabeled Data
This paper proposes a semi-supervised boosting approach to improve statistical word alignment with limited labeled data and large amounts of unlabeled data. The proposed approach ...
Hua Wu, Haifeng Wang, Zhan-yi Liu
ICML
2003
IEEE
14 years 9 months ago
Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions
An approach to semi-supervised learning is proposed that is based on a Gaussian random field model. Labeled and unlabeled data are represented as vertices in a weighted graph, wit...
Xiaojin Zhu, Zoubin Ghahramani, John D. Lafferty
JMLR
2010
119views more  JMLR 2010»
13 years 3 months ago
Semi-Supervised Learning via Generalized Maximum Entropy
Various supervised inference methods can be analyzed as convex duals of the generalized maximum entropy (MaxEnt) framework. Generalized MaxEnt aims to find a distribution that max...
Ayse Erkan, Yasemin Altun
SSPR
2004
Springer
14 years 2 months ago
Learning from General Label Constraints
Most machine learning algorithms are designed either for supervised or for unsupervised learning, notably classification and clustering. Practical problems in bioinformatics and i...
Tijl De Bie, Johan A. K. Suykens, Bart De Moor
ICMCS
2006
IEEE
131views Multimedia» more  ICMCS 2006»
14 years 3 months ago
Self-Supervised Learning for Robust Video Indexing
The performance of video analysis and indexing algorithms strongly depends on the type, content and recording characteristics of the analyzed video. Current video indexing approac...
Ralph Ewerth, Bernd Freisleben