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» Testing homogeneity of a large data set by bootstrapping
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NIPS
2008
13 years 8 months ago
Correlated Bigram LSA for Unsupervised Language Model Adaptation
We present a correlated bigram LSA approach for unsupervised LM adaptation for automatic speech recognition. The model is trained using efficient variational EM and smoothed using...
Yik-Cheung Tam, Tanja Schultz
BMCBI
2005
78views more  BMCBI 2005»
13 years 7 months ago
Correlation test to assess low-level processing of high-density oligonucleotide microarray data
Background: There are currently a number of competing techniques for low-level processing of oligonucleotide array data. The choice of technique has a profound effect on subsequen...
Alexander Ploner, Lance D. Miller, Per Hall, Jonas...
JMLR
2010
108views more  JMLR 2010»
13 years 2 months ago
Tree Decomposition for Large-Scale SVM Problems
To handle problems created by large data sets, we propose a method that uses a decision tree to decompose a given data space and train SVMs on the decomposed regions. Although the...
Fu Chang, Chien-Yang Guo, Xiao-Rong Lin, Chi-Jen L...
ICTAI
2002
IEEE
14 years 10 days ago
Data Mining for Selective Visualization of Large Spatial Datasets
Data mining is the process of extracting implicit, valuable, and interesting information from large sets of data. Visualization is the process of visually exploring data for patte...
Shashi Shekhar, Chang-Tien Lu, Pusheng Zhang, Ruli...
CVPR
2011
IEEE
13 years 3 months ago
Large-Scale Live Active Learning: Training Object Detectors with Crawled Data and Crowds
Active learning and crowdsourcing are promising ways to efficiently build up training sets for object recognition, but thus far techniques are tested in artificially controlled ...
Sudheendra Vijayanarasimhan, Kristen Grauman