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» Learning Useful Horn Approximations
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NIPS
2007
15 years 2 months ago
The Tradeoffs of Large Scale Learning
This contribution develops a theoretical framework that takes into account the effect of approximate optimization on learning algorithms. The analysis shows distinct tradeoffs for...
Léon Bottou, Olivier Bousquet
107
Voted
IUI
2005
ACM
15 years 6 months ago
Intelligent data entry assistant for XML using ensemble learning
XML has emerged as the primary standard of data representation and data exchange [13]. Although many software tools exist to assist the XML implementation process, data must be ma...
Danico Lee, Costas Tsatsoulis
ICML
2004
IEEE
16 years 1 months ago
Semi-supervised learning using randomized mincuts
In many application domains there is a large amount of unlabeled data but only a very limited amount of labeled training data. One general approach that has been explored for util...
Avrim Blum, John D. Lafferty, Mugizi Robert Rweban...
BMCBI
2010
154views more  BMCBI 2010»
15 years 26 days ago
Candidate gene prioritization by network analysis of differential expression using machine learning approaches
Background: Discovering novel disease genes is still challenging for diseases for which no prior knowledge - such as known disease genes or disease-related pathways - is available...
Daniela Nitsch, Joana P. Gonçalves, Fabian ...
110
Voted
NIPS
1998
15 years 2 months ago
Learning Nonlinear Dynamical Systems Using an EM Algorithm
The Expectation Maximization EM algorithm is an iterative procedure for maximum likelihood parameter estimation from data sets with missing or hidden variables 2 . It has been app...
Zoubin Ghahramani, Sam T. Roweis