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January 1, 2021IEEE Transactions on Pattern Analysis and Machine Intelligence

A Survey on Curriculum Learning

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Authors

XWXin WangYCYudong ChenWZWenwu Zhu

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Overview

Survey reviews curriculum learning techniques and applications, highlighting design strategies and future directions.

Key Points

  • The aim is to comprehensively review curriculum learning, its motivations, definitions, theories, and applications in machine learning.
  • Reviewed various curriculum learning designs and methodologies.
  • Categorized automatic curriculum learning methodologies into four groups: Self-paced Learning, Transfer Teacher, RL Teacher, and Other Automatic CL.
  • Analyzed relationships connecting curriculum learning with other machine learning concepts.
  • Demonstrated curriculum learning improves generalization and convergence in various machine learning applications.
  • Summarized principles for designing effective curriculum learning strategies for practical use.
  • Identified challenges and potential future research directions in curriculum learning.

Cite This Study

Wang et al. (2021) studied this question.

synapsesocial.com/papers/6a0fdf0a5725bbd5cc602e72https://doi.org/10.1109/tpami.2021.3069908
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