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IDA
2005
Springer
16 years 14 days ago
Removing Statistical Biases in Unsupervised Sequence Learning
Unsupervised sequence learning is important to many applications. A learner is presented with unlabeled sequential data, and must discover sequential patterns that characterize the...
Yoav Horman, Gal A. Kaminka
BIBE
2005
IEEE
16 years 18 days ago
Using Data Mining Techniques to Learn Layouts of Flat-File Biological Datasets
One of the major problems in biological data integration is that many data sources are stored as flat-files, with a variety of different layouts. Integrating data from such sour...
Kaushik Sinha, Xuan Zhang, Ruoming Jin, Gagan Agra...