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When Does Curriculum Learning Help? A Theoretical Perspective

NeurIPS 2025 · Optimization › Implicit bias and generalization · approach: Stability-based generalization analysis · 0 citations (OpenAlex)

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Develops a theoretical framework for curriculum learning based on biased regularized empirical risk minimization, identifying conditions under which curriculum learning provably helps.

Problem

Curriculum learning is empirically effective for training efficiency and generalization, but its theoretical underpinnings are underexplored.

Approach

Models curriculum learning as biased regularized empirical risk minimization and derives conditions under which curriculum ordering provably improves learning.

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