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ICML
2002
IEEE
16 years 7 months ago
Active + Semi-supervised Learning = Robust Multi-View Learning
In a multi-view problem, the features of the domain can be partitioned into disjoint subsets (views) that are sufficient to learn the target concept. Semi-supervised, multi-view a...
Ion Muslea, Steven Minton, Craig A. Knoblock
ICALT
2008
IEEE
16 years 1 months ago
Interaction Analysis as a Multi-Support Approach of Social Computing for Learning, in the "Collaborative Era": Lessons Learned b
Apparently computer technology is shifting its focus, with individual users not being the main target any more. The evolution of Web 2.0 technologies is promoting the development ...
Tharrenos Bratitsis, Angelique Dimitracopoulou
ABIALS
2008
Springer
15 years 9 months ago
Anticipatory Learning Classifier Systems and Factored Reinforcement Learning
Factored Reinforcement Learning (frl) is a new technique to solve Factored Markov Decision Problems (fmdps) when the structure of the problem is not known in advance. Like Anticipa...
Olivier Sigaud, Martin V. Butz, Olga Kozlova, Chri...
ECTEL
2010
Springer
15 years 8 months ago
Deep Learning Design for Sustainable Innovation within Shifting Learning Landscapes
Changes in the underpinning technologies for TEL is occurring at a pace that we have never before experienced, and this is unlikely to slow down. This necessitates a broader and mo...
Andrew Ravenscroft, Tom Boyle, John Cook, Andreas ...
ICWL
2010
Springer
15 years 4 months ago
Not Yet Ready for Everyone: An Experience Report about a Personal Learning Environment for Language Learning
A Personal Learning Environment (PLE) is a mash-up of learning services. It enables students and teachers to assemble a work environment that is adapted to a domain and specific in...
Carsten Ullrich, Ruimin Shen, Denis Gillet