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PKDD
2009
Springer
153views Data Mining» more  PKDD 2009»
16 years 21 days ago
Subspace Regularization: A New Semi-supervised Learning Method
Most existing semi-supervised learning methods are based on the smoothness assumption that data points in the same high density region should have the same label. This assumption, ...
Yan-Ming Zhang, Xinwen Hou, Shiming Xiang, Cheng-L...
MICAI
2007
Springer
16 years 9 days ago
Weighted Instance-Based Learning Using Representative Intervals
Instance-based learning algorithms are widely used due to their capacity to approximate complex target functions; however, the performance of this kind of algorithms degrades signi...
Octavio Gómez, Eduardo F. Morales, Jes&uacu...
GECCO
2005
Springer
155views Optimization» more  GECCO 2005»
15 years 11 months ago
Co-evolving recurrent neurons learn deep memory POMDPs
Recurrent neural networks are theoretically capable of learning complex temporal sequences, but training them through gradient-descent is too slow and unstable for practical use i...
Faustino J. Gomez, Jürgen Schmidhuber
SIGECOM
2004
ACM
135views ECommerce» more  SIGECOM 2004»
15 years 11 months ago
Applying learning algorithms to preference elicitation
We consider the parallels between the preference elicitation problem in combinatorial auctions and the problem of learning an unknown function from learning theory. We show that l...
Sébastien Lahaie, David C. Parkes
CHI
1998
ACM
15 years 10 months ago
New Media, New Practices: Experiences in Open Learning Course Design
We explore some of the complex issues surrounding the design and use of multimedia and Internet-based learning resources in distance education courses. We do so by analysing our e...
Tamara Sumner, Josie Taylor