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» Learning Functions from Imperfect Positive Data
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ICML
2005
IEEE
14 years 10 months ago
Learning to rank using gradient descent
We investigate using gradient descent methods for learning ranking functions; we propose a simple probabilistic cost function, and we introduce RankNet, an implementation of these...
Christopher J. C. Burges, Tal Shaked, Erin Renshaw...
BMCBI
2008
141views more  BMCBI 2008»
13 years 10 months ago
Functional discrimination of membrane proteins using machine learning techniques
Background: Discriminating membrane proteins based on their functions is an important task in genome annotation. In this work, we have analyzed the characteristic features of amin...
M. Michael Gromiha, Yukimitsu Yabuki
HUMO
2000
Springer
14 years 1 months ago
Specialized Mappings and the Estimation of Human Body Pose from a Single Image
We present an approach for recovering articulated body pose from single monocular images using the Specialized Mappings Architecture (SMA), a non-linear supervised learning archit...
Rómer Rosales, Stan Sclaroff
NIPS
1994
13 years 11 months ago
Combining Estimators Using Non-Constant Weighting Functions
This paper discusses the linearly weighted combination of estimators in which the weighting functions are dependent on the input. We show that the weighting functions can be deriv...
Volker Tresp, Michiaki Taniguchi
COLT
2006
Springer
14 years 1 months ago
Memory-Limited U-Shaped Learning
U-shaped learning is a learning behaviour in which the learner first learns a given target behaviour, then unlearns it and finally relearns it. Such a behaviour, observed by psych...
Lorenzo Carlucci, John Case, Sanjay Jain, Frank St...