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IEEEPACT
2008
IEEE
16 years 16 days ago
Feature selection and policy optimization for distributed instruction placement using reinforcement learning
Communication overheads are one of the fundamental challenges in a multiprocessor system. As the number of processors on a chip increases, communication overheads and the distribu...
Katherine E. Coons, Behnam Robatmili, Matthew E. T...
NLPRS
2001
Springer
15 years 10 months ago
A Bayesian Approach to Semi-Supervised Learning
Recent research in automated learning has focused on algorithms that learn from a combination of tagged and untagged data. Such algorithms can be referred to as semi-supervised in...
Rebecca F. Bruce
GECCO
2008
Springer
126views Optimization» more  GECCO 2008»
15 years 7 months ago
Swarm intelligence in e-learning: a learning object sequencing agent based on competencies
In e-learning initiatives content creators are usually required to arrange a set of learning resources in order to present them in a comprehensive way to the learner. Course mater...
Luis de Marcos, José-Javier Martínez...
TNN
1998
111views more  TNN 1998»
15 years 5 months ago
Asymptotic distributions associated to Oja's learning equation for neural networks
— In this paper, we perform a complete asymptotic performance analysis of the stochastic approximation algorithm (denoted subspace network learning algorithm) derived from Oja’...
Jean Pierre Delmas, Jean-Francois Cardos
UAI
2004
15 years 7 months ago
A Bayesian Approach toward Active Learning for Collaborative Filtering
Collaborative filtering is a useful technique for exploiting the preference patterns of a group of users to predict the utility of items for the active user. In general, the perfo...
Rong Jin, Luo Si