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ICDM
2003
IEEE
210views Data Mining» more  ICDM 2003»
15 years 11 months ago
CBC: Clustering Based Text Classification Requiring Minimal Labeled Data
Semi-supervised learning methods construct classifiers using both labeled and unlabeled training data samples. While unlabeled data samples can help to improve the accuracy of trai...
Hua-Jun Zeng, Xuanhui Wang, Zheng Chen, Hongjun Lu...
MMM
2012
Springer
294views Multimedia» more  MMM 2012»
14 years 1 months ago
Improving Cluster Selection and Event Modeling in Unsupervised Mining for Automatic Audiovisual Video Structuring
Abstract. Can we discover audio-visually consistent events from videos in a totally unsupervised manner? And, how to mine videos with different genres? In this paper we present our...
Anh-Phuong Ta, Mathieu Ben, Guillaume Gravier
CVPR
2001
IEEE
16 years 7 months ago
Small Sample Learning during Multimedia Retrieval using BiasMap
All positive examples are alike; each negative example is negative in its own way. During interactive multimedia information retrieval, the number of training samples fed-back by ...
Xiang Sean Zhou, Thomas S. Huang
ICML
2007
IEEE
16 years 6 months ago
Optimal dimensionality of metric space for classification
In many real-world applications, Euclidean distance in the original space is not good due to the curse of dimensionality. In this paper, we propose a new method, called Discrimina...
Wei Zhang, Xiangyang Xue, Zichen Sun, Yue-Fei Guo,...
ICML
2007
IEEE
16 years 6 months ago
Two-view feature generation model for semi-supervised learning
We consider a setting for discriminative semisupervised learning where unlabeled data are used with a generative model to learn effective feature representations for discriminativ...
Rie Kubota Ando, Tong Zhang