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Rather than produce clear-cut answers to well-defined problems, research on future environmental policy issues requires a different approach whereby researchers are partners in joint learning processes among stakeholders, policy makers, NGOs (Non-Governmental Organisations) and industry.
Yang et al. proposed joint learning [6] and coupled learning [23] algorithms to train coupled dictionaries.
We compared our joint learning method kDDN with four peer methods: 1) DDN (independent learning) [ 13], 2) csLearner (joint learning) [ 15], 3) Meinshausen's method (independent learning) [ 23], and 4) Tesla (joint learning) [ 18]. csLearner can learn more than two networks but we restricted the condition to two.
> We present experimental results to evaluate the performance of our joint learning approach.
Most ACCs organize expert meetings and joint learning platforms to share knowledge and discuss knowledge application.
First, we have proposed a joint learning approach to detecting biomolecular events described in text.
We compare our joint learning approach against two baseline approaches (models).
Facilitating structures, such as live webinar technology and workshops, promoted discussions and joint learning.
Without overcoming this mutual distrust, joint learning is unlikely to be successful.
GAVI could play a role in convening graduating countries for such joint learning.
The first verification was organized as peer review of districts to facilitate joint learning.
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