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ICML
2007
IEEE
14 years 9 months ago
Simple, robust, scalable semi-supervised learning via expectation regularization
Although semi-supervised learning has been an active area of research, its use in deployed applications is still relatively rare because the methods are often difficult to impleme...
Gideon S. Mann, Andrew McCallum
COLT
2010
Springer
13 years 6 months ago
Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
We present a new family of subgradient methods that dynamically incorporate knowledge of the geometry of the data observed in earlier iterations to perform more informative gradie...
John Duchi, Elad Hazan, Yoram Singer
CIKM
2011
Springer
12 years 8 months ago
Toward interactive training and evaluation
Machine learning often relies on costly labeled data, and this impedes its application to new classification and information extraction problems. This has motivated the developme...
Gregory Druck, Andrew McCallum
ICGI
2000
Springer
14 years 6 days ago
Counting Extensional Differences in BC-Learning
Let BC be the model of behaviourally correct function learning as introduced by B
Frank Stephan, Sebastiaan Terwijn
AE
2003
Springer
14 years 1 months ago
An Agent Model for First Price and Second Price Private Value Auctions
The aim of this research is to develop an adaptive agent based model of auction scenarios commonly used in auction theory to help understand how competitors in auctions reach equil...
Anthony J. Bagnall, Iain Toft