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ESANN
2007
14 years 11 months ago
How to process uncertainty in machine learning?
Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...
Barbara Hammer, Thomas Villmann
CCGRID
2005
IEEE
15 years 3 months ago
Enabling technologies for future learning scenarios: the semantic grid for human learning
In this paper, starting from the limitations and constrains of traditional human learning approaches, we outline new suitable approaches to education and training in future knowle...
Angelo Gaeta, Pierluigi Ritrovato, Francesco Orciu...
CORR
2010
Springer
103views Education» more  CORR 2010»
14 years 9 months ago
Asymptotic Learning Curve and Renormalizable Condition in Statistical Learning Theory
Bayes statistics and statistical physics have the common mathematical structure, where the log likelihood function corresponds to the random Hamiltonian. Recently, it was discovere...
Sumio Watanabe
COLT
1998
Springer
15 years 1 months ago
Self Bounding Learning Algorithms
Most of the work which attempts to give bounds on the generalization error of the hypothesis generated by a learning algorithm is based on methods from the theory of uniform conve...
Yoav Freund
72
Voted
ECIS
2003
14 years 11 months ago
Re-negotiating protocols: a way to integrate groupware in collaborative learning settings
Research is being done within the Computer Supported Collaborative Learning community to investigate how to apply the approach of Problem Oriented Project Pedagogy in distance lea...
Pernille Bjørn Rasmussen