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168
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JMLR
2010
143views more  JMLR 2010»
14 years 11 months ago
Incremental Sigmoid Belief Networks for Grammar Learning
We propose a class of Bayesian networks appropriate for structured prediction problems where the Bayesian network's model structure is a function of the predicted output stru...
James Henderson, Ivan Titov
BMCBI
2006
94views more  BMCBI 2006»
15 years 5 months ago
Noise-injected neural networks show promise for use on small-sample expression data
Background: Overfitting the data is a salient issue for classifier design in small-sample settings. This is why selecting a classifier from a constrained family of classifiers, on...
Jianping Hua, James Lowey, Zixiang Xiong, Edward R...
145
Voted
NN
2008
Springer
153views Neural Networks» more  NN 2008»
15 years 4 months ago
A biologically motivated visual memory architecture for online learning of objects
We present a biologically motivated architecture for object recognition that is based on a hierarchical feature-detection model in combination with a memory architecture that impl...
Stephan Kirstein, Heiko Wersing, Edgar Körner
181
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BMCBI
2005
198views more  BMCBI 2005»
15 years 4 months ago
Clustering protein sequences with a novel metric transformed from sequence similarity scores and sequence alignments with neural
Background: The sequencing of the human genome has enabled us to access a comprehensive list of genes (both experimental and predicted) for further analysis. While a majority of t...
Qicheng Ma, Gung-Wei Chirn, Richard Cai, Joseph D....
ICANN
2003
Springer
15 years 10 months ago
A Comparison of Model Aggregation Methods for Regression
Combining machine learning models is a means of improving overall accuracy.Various algorithms have been proposed to create aggregate models from other models, and two popular examp...
Zafer Barutçuoglu