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In this paper, we introduce a framework for learning biped locomotion using dynamical movement primitives based on non-linear oscillators.
The main purpose of this model is to build a framework for learning algorithms, which will be used in the adaptive driver assistance system.
In [18], Mairal et al. presented a framework for learning multiscale sparse representations of color images and video with overcomplete dictionaries.
The proposed solution is a framework for learning Terminological Decision Trees from examples described in an ontological knowledge base, to be used for performing instance classifications.
Generally speaking, these national curriculums for early childhood lay out a framework for learning that guides local implementation of each nation's government-funded preschool program (Alvestad and Samuelsson 1999; Flottman and Page 2012; May 2008).
Much more work has been done in robot learning, e.g., Knox et al. [69] presented a case study of applying a framework for learning from human feedback to a physically embodied robot.
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We propose and analyze a novel framework for learning sparse representations based on two statistical techniques: kernel smoothing and marginal regression.
Although the model does contain challenges, it represents a generic framework for learning and teaching that is flexible for further development and applicable to many subjects and levels.
The feasibility of our approach is proven exemplarily by stairs, and a generic framework for learning other building parts is discussed.
This article elaborates a conceptual framework for learning organizations, through the introduction of change concepts and the creation of learning teams, and reports on a case that illustrates this framework.
The purpose of this research is to design of a framework for cooperative learning through web utilizing data mining technique to group learners.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com