Sentence examples for final learned from inspiring English sources

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As a result, the final learned model can effectively find out the matched target to the anchor image among a number of candidates in the gallery image set by learning discriminative and stable feature representations.

A proper choice and design of function approximator is critical for convergence of the iteration and the quality of final learned control policy, because an approximation error can grow quickly in the loop of optimization and function approximation.

Moreover, these figures also show that the ALM-DL has another well-posed property, i.e., it is insensitive to initialization because the final learned dictionaries are very similar to each other regardless of the atom location (seen from Figures 6e and 7e), while K-SVD depends too much on the initialization.

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Consequently, the final learning result is more creditable.

Traditional summative evaluation only considers final learning outcomes, without concerning the learning processes of learners.

The possibility of predicting final learning performance provides useful information to improve student's learning activities during the course.

Sobel edge images are used for final learning and recognition, just like in the case of television.

The fifth stage was the focus group discussion where all teachers teaching ENGLCOM reviewed and refined the final learning outcomes.

Similar to the authoring tool, participants can create or edit artifacts on the center learning space to represent their intermediate or final learning outcome.

When designing a PBL process, teachers need to figure out which activities are appropriate for which phase or what kinds of artifacts should be provided as temporary or final learning outcomes for certain phases.

The following decreasing functions are common: begin{aligned} sigma (t)=sigma _{i}left( frac{sigma _{f}}{sigma _{i}}right) ^{t/t_{f}},quad eta (t)=eta _{i}left( frac{eta _{f}}{eta _{i}}right) ^{t/t_{f}}, end{aligned} (4 where (sigma _i) and (sigma _f) are respectively the initial and final neighborhood width and (eta _i) and (eta _f) the initial and final learning rate.

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