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PAMI
2011
14 years 6 months ago
Semi-Supervised Learning via Regularized Boosting Working on Multiple Semi-Supervised Assumptions
—Semi-supervised learning concerns the problem of learning in the presence of labeled and unlabeled data. Several boosting algorithms have been extended to semi-supervised learni...
Ke Chen, Shihai Wang
EMNLP
2009
14 years 9 months ago
Semi-Supervised Learning for Semantic Relation Classification using Stratified Sampling Strategy
This paper presents a new approach to selecting the initial seed set using stratified sampling strategy in bootstrapping-based semi-supervised learning for semantic relation class...
Longhua Qian, Guodong Zhou, Fang Kong, Qiaoming Zh...
CVPR
2005
IEEE
16 years 1 months ago
Semi-Supervised Cross Feature Learning for Semantic Concept Detection in Videos
For large scale automatic semantic video characterization, it is necessary to learn and model a large number of semantic concepts. But a major obstacle to this is the insufficienc...
Rong Yan, Milind R. Naphade
EMNLP
2010
14 years 9 months ago
A Semi-Supervised Approach to Improve Classification of Infrequent Discourse Relations Using Feature Vector Extension
Several recent discourse parsers have employed fully-supervised machine learning approaches. These methods require human annotators to beforehand create an extensive training corp...
Hugo Hernault, Danushka Bollegala, Mitsuru Ishizuk...
TIT
2008
224views more  TIT 2008»
14 years 11 months ago
Graph-Based Semi-Supervised Learning and Spectral Kernel Design
We consider a framework for semi-supervised learning using spectral decomposition-based unsupervised kernel design. We relate this approach to previously proposed semi-supervised l...
Rie Johnson, Tong Zhang