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ICML
2005
IEEE
16 years 4 months ago
Healing the relevance vector machine through augmentation
The Relevance Vector Machine (RVM) is a sparse approximate Bayesian kernel method. It provides full predictive distributions for test cases. However, the predictive uncertainties ...
Carl Edward Rasmussen, Joaquin Quiñonero Ca...
ICML
2008
IEEE
16 years 4 months ago
A decoupled approach to exemplar-based unsupervised learning
A recent trend in exemplar based unsupervised learning is to formulate the learning problem as a convex optimization problem. Convexity is achieved by restricting the set of possi...
Gökhan H. Bakir, Sebastian Nowozin
ICML
2005
IEEE
16 years 4 months ago
A general regression technique for learning transductions
The problem of learning a transduction, that is a string-to-string mapping, is a common problem arising in natural language processing and computational biology. Previous methods ...
Corinna Cortes, Mehryar Mohri, Jason Weston
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ICML
2009
IEEE
15 years 10 months ago
Learning linear dynamical systems without sequence information
Virtually all methods of learning dynamic systems from data start from the same basic assumption: that the learning algorithm will be provided with a sequence, or trajectory, of d...
Tzu-Kuo Huang, Jeff Schneider
ICALT
2003
IEEE
15 years 8 months ago
Constructivism vs. Objectivism: Where is difference for Designers of e-Learning Environments?
This position paper discusses different philosophical views of learning and the consequences of these different epistemologies on the design of online learning environments. Acade...
Miguel Baptista Nunes, Maggie McPherson