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ICASSP
2009
IEEE
16 years 1 months ago
Using collective information in semi-supervised learning for speech recognition
Training accurate acoustic models typically requires a large amount of transcribed data, which can be expensive to obtain. In this paper, we describe a novel semi-supervised learn...
Balakrishnan Varadarajan, Dong Yu, Li Deng, Alex A...
ICCV
2007
IEEE
16 years 1 months ago
Learning The Discriminative Power-Invariance Trade-Off
We investigate the problem of learning optimal descriptors for a given classification task. Many hand-crafted descriptors have been proposed in the literature for measuring visua...
Manik Varma, Debajyoti Ray
ISMIS
2005
Springer
16 years 18 days ago
Scalable Inductive Learning on Partitioned Data
With the rapid advancement of information technology, scalability has become a necessity for learning algorithms to deal with large, real-world data repositories. In this paper, sc...
Qijun Chen, Xindong Wu, Xingquan Zhu
ECML
2003
Springer
16 years 9 days ago
Pairwise Preference Learning and Ranking
We consider supervised learning of a ranking function, which is a mapping from instances to total orders over a set of labels (options). The training information consists of exampl...
Johannes Fürnkranz, Eyke Hüllermeier
ECML
2006
Springer
15 years 10 months ago
Unsupervised Multiple-Instance Learning for Functional Profiling of Genomic Data
Multiple-instance learning (MIL) is a popular concept among the AI community to support supervised learning applications in situations where only incomplete knowledge is available....
Corneliu Henegar, Karine Clément, Jean-Dani...