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136
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IJON
2008
133views more  IJON 2008»
15 years 1 months ago
A multi-objective approach to RBF network learning
The problem of inductive supervised learning is discussed in this paper within the context of multi-objective (MOBJ) optimization. The smoothness-based apparent (effective) comple...
Illya Kokshenev, Antônio de Pádua Bra...
120
Voted
HICSS
2008
IEEE
147views Biometrics» more  HICSS 2008»
15 years 9 months ago
Can Peer-to-Peer Networks Facilitate Information Sharing in Collaborative Learning?
Many peer-to-peer (P2P) networks have been widely used for file sharing. A peer acts both as a content provider and a consumer, and is granted autonomy to decide what content, wit...
Fu-ren Lin, Sheng-cheng Lin, Ying-fen Wang
142
Voted
ICMLA
2010
15 years 21 days ago
Ensembles of Neural Networks for Robust Reinforcement Learning
Reinforcement learning algorithms that employ neural networks as function approximators have proven to be powerful tools for solving optimal control problems. However, their traini...
Alexander Hans, Steffen Udluft
147
Voted
JMLR
2010
140views more  JMLR 2010»
14 years 9 months ago
Learning Non-Stationary Dynamic Bayesian Networks
Learning dynamic Bayesian network structures provides a principled mechanism for identifying conditional dependencies in time-series data. An important assumption of traditional D...
Joshua W. Robinson, Alexander J. Hartemink
114
Voted
ECTEL
2008
Springer
15 years 4 months ago
Knowledge Practices Environment: Design and Application of Technology for Trialogical Learning
Current networked society present learners with challenges that cannot be sufficiently coped with in educational contexts that are characterized by transmission or participation ep...
Patrick Sins, Merja Bauters, Crina Damsa