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Among these, an effective technique is local learning.
We should all want to live like a local, learning about other cultures from the people who live in the region.
Packages of services are pilot tested and effectiveness is determined through local learning.
Developing countries have technological activities that are important locally but not significant at international level (imitation, local learning, adaptation of foreign innovations).
Online NFMs adopt a local learning approach and are able to adapt to changes continuously.
Secondly, a local learning method using a competitive penalized method is developed to refine the solution.
A local learning mechanism is used to improve local exploitation ability in the historical best population.
The latter is based on a local learning algorithm, called the Lazy Learning (LL) algorithm.
This method is based on the local learning and recursive modeling framework.
To better understand random backpropagation, we first connect it to the notions of local learning and learning channels.
The local learning algorithm also required a shorter training time compared to a global learning NFS model.
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