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ICML
2008
IEEE
14 years 10 months ago
Fully distributed EM for very large datasets
In EM and related algorithms, E-step computations distribute easily, because data items are independent given parameters. For very large data sets, however, even storing all of th...
Jason Wolfe, Aria Haghighi, Dan Klein
PRIS
2004
13 years 10 months ago
Learning Text Extraction Rules, without Ignoring Stop Words
Information Extraction (IE) from text /web documents has become an important application area of AI. As the number of web sites and documents has grown dramatically, the users need...
João Cordeiro, Pavel Brazdil
JMLR
2010
155views more  JMLR 2010»
13 years 7 months ago
Approximate Tree Kernels
Convolution kernels for trees provide simple means for learning with tree-structured data. The computation time of tree kernels is quadratic in the size of the trees, since all pa...
Konrad Rieck, Tammo Krueger, Ulf Brefeld, Klaus-Ro...
ICML
2006
IEEE
14 years 10 months ago
Learning a kernel function for classification with small training samples
When given a small sample, we show that classification with SVM can be considerably enhanced by using a kernel function learned from the training data prior to discrimination. Thi...
Tomer Hertz, Aharon Bar-Hillel, Daphna Weinshall
IDA
2002
Springer
13 years 8 months ago
Evolutionary model selection in unsupervised learning
Feature subset selection is important not only for the insight gained from determining relevant modeling variables but also for the improved understandability, scalability, and pos...
YongSeog Kim, W. Nick Street, Filippo Menczer