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AAAI
1998
13 years 10 months ago
Learning to Classify Text from Labeled and Unlabeled Documents
In many important text classification problems, acquiring class labels for training documents is costly, while gathering large quantities of unlabeled data is cheap. This paper sh...
Kamal Nigam, Andrew McCallum, Sebastian Thrun, Tom...
MM
2010
ACM
132views Multimedia» more  MM 2010»
13 years 9 months ago
One person labels one million images
Targeting the same objective of alleviating the manual work as automatic annotation, in this paper, we propose a novel framework with minimal human effort to manually annotate a l...
Jinhui Tang, Qiang Chen, Shuicheng Yan, Tat-Seng C...
KDD
2006
ACM
162views Data Mining» more  KDD 2006»
14 years 9 months ago
Simultaneous record detection and attribute labeling in web data extraction
Recent work has shown the feasibility and promise of templateindependent Web data extraction. However, existing approaches use decoupled strategies ? attempting to do data record ...
Jun Zhu, Zaiqing Nie, Ji-Rong Wen, Bo Zhang, Wei-Y...
FOIKS
2008
Springer
14 years 5 months ago
Cost-minimising strategies for data labelling : optimal stopping and active learning
Supervised learning deals with the inference of a distribution over an output or label space $\CY$ conditioned on points in an observation space $\CX$, given a training dataset $D$...
Christos Dimitrakakis, Christian Savu-Krohn
CVPR
2011
IEEE
13 years 5 months ago
Learning A Discriminative Dictionary for Sparse Coding via Label Consistent K-SVD
A label consistent K-SVD (LC-KSVD) algorithm to learn a discriminative dictionary for sparse coding is presented. In addition to using class labels of training data, we also assoc...
Zhuolin Jiang, Zhe Lin, Larry Davis