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» Spectral Algorithms for Supervised Learning
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ACL
2012
13 years 23 hour ago
Spectral Learning of Latent-Variable PCFGs
We introduce a spectral learning algorithm for latent-variable PCFGs (Petrov et al., 2006). Under a separability (singular value) condition, we prove that the method provides cons...
Shay B. Cohen, Karl Stratos, Michael Collins, Dean...
BMCBI
2010
176views more  BMCBI 2010»
14 years 9 months ago
TargetSpy: a supervised machine learning approach for microRNA target prediction
Background: Virtually all currently available microRNA target site prediction algorithms require the presence of a (conserved) seed match to the 5' end of the microRNA. Recen...
Martin Sturm, Michael Hackenberg, David Langenberg...
SYNASC
2006
IEEE
211views Algorithms» more  SYNASC 2006»
15 years 3 months ago
HTML Pattern Generator--Automatic Data Extraction from Web Pages
Existing methods of information extraction from HTML documents include manual approach, supervised learning and automatic techniques. The manual method has high precision and reca...
Mirel Cosulschi, Adrian Giurca, Bogdan Udrescu, Ni...
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AAAI
2008
14 years 12 months ago
Semi-Supervised Ensemble Ranking
Ranking plays a central role in many Web search and information retrieval applications. Ensemble ranking, sometimes called meta-search, aims to improve the retrieval performance b...
Steven C. H. Hoi, Rong Jin
GECCO
2005
Springer
158views Optimization» more  GECCO 2005»
15 years 3 months ago
Applying both positive and negative selection to supervised learning for anomaly detection
This paper presents a novel approach of applying both positive selection and negative selection to supervised learning for anomaly detection. It first learns the patterns of the n...
Xiaoshu Hang, Honghua Dai