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Deep curriculum learning optimization
2020
SN Computer Science
We describe a quantitative and practical framework to integrate curriculum learning (CL) into deep learning training pipeline to improve feature learning in deep feed-forward networks. The framework has several unique characteristics: (1) dynamicity-it proposes a set of batch-level training strategies (syllabi or curricula) that are sensitive to data complexity (2) adaptivity-it dynamically estimates the effectiveness of a given strategy and performs objective comparison with alternative
doi:10.1007/s42979-020-00251-7
fatcat:xzs7gigpizaejaezdkeodfrqqu