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» Nonlinear principal component analysis of noisy data
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NIPS
1997
14 years 11 months ago
Learning Generative Models with the Up-Propagation Algorithm
Up-propagation is an algorithm for inverting and learning neural network generative models. Sensory input is processed by inverting a model that generates patterns from hidden var...
Jong-Hoon Oh, H. Sebastian Seung
BMCBI
2008
132views more  BMCBI 2008»
14 years 9 months ago
Very Important Pool (VIP) genes - an application for microarray-based molecular signatures
Background: Advances in DNA microarray technology portend that molecular signatures from which microarray will eventually be used in clinical environments and personalized medicin...
Zhenqiang Su, Huixiao Hong, Hong Fang, Leming M. S...
DEBU
2008
186views more  DEBU 2008»
14 years 9 months ago
A Survey of Collaborative Recommendation and the Robustness of Model-Based Algorithms
The open nature of collaborative recommender systems allows attackers who inject biased profile data to have a significant impact on the recommendations produced. Standard memory-...
Jeff J. Sandvig, Bamshad Mobasher, Robin D. Burke
BMCBI
2006
139views more  BMCBI 2006»
14 years 9 months ago
DNA Molecule Classification Using Feature Primitives
Background: We present a novel strategy for classification of DNA molecules using measurements from an alpha-Hemolysin channel detector. The proposed approach provides excellent c...
Raja Tanveer Iqbal, Matthew Landry, Stephen Winter...
MLMI
2007
Springer
15 years 3 months ago
To Separate Speech
The PASCAL Speech Separation Challenge (SSC) is based on a corpus of sentences from the Wall Street Journal task read by two speakers simultaneously and captured with two circular ...
John W. McDonough, Ken'ichi Kumatani, Tobias Gehri...