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» Predicting diverse subsets using structural SVMs
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WWW
2009
ACM
15 years 10 months ago
Enhancing diversity, coverage and balance for summarization through structure learning
Document summarization plays an increasingly important role with the exponential growth of documents on the Web. Many supervised and unsupervised approaches have been proposed to ...
Liangda Li, Ke Zhou, Gui-Rong Xue, Hongyuan Zha, Y...
PKDD
2007
Springer
91views Data Mining» more  PKDD 2007»
15 years 3 months ago
Domain Adaptation of Conditional Probability Models Via Feature Subsetting
The goal in domain adaptation is to train a model using labeled data sampled from a domain different from the target domain on which the model will be deployed. We exploit unlabel...
Sandeepkumar Satpal, Sunita Sarawagi
85
Voted
CEC
2009
IEEE
15 years 25 days ago
Using genetic programming to obtain implicit diversity
—When performing predictive data mining, the use of ensembles is known to increase prediction accuracy, compared to single models. To obtain this higher accuracy, ensembles shoul...
Ulf Johansson, Cecilia Sönströd, Tuve L&...
BMCBI
2008
114views more  BMCBI 2008»
14 years 9 months ago
Combining classifiers for improved classification of proteins from sequence or structure
Background: Predicting a protein's structural or functional class from its amino acid sequence or structure is a fundamental problem in computational biology. Recently, there...
Iain Melvin, Jason Weston, Christina S. Leslie, Wi...
BMCBI
2006
143views more  BMCBI 2006»
14 years 9 months ago
Application of protein structure alignments to iterated hidden Markov model protocols for structure prediction
Background: One of the most powerful methods for the prediction of protein structure from sequence information alone is the iterative construction of profile-type models. Because ...
Eric D. Scheeff, Philip E. Bourne