Uses CMA-ES to evolve optimal masking parameters for I-JEPA self-supervised pretraining.
Fitness is evaluated via kNN accuracy on CIFAR-100 after short pretraining runs.
Paper motivation:
I-JEPA (arxiv:2301.08243) showed masking params swing accuracy by 45+ points
FER paper (arxiv:2505.11581) showed evolution produces better representations than SGD
This combines both: evolving the masking strategy that guides SGD-based JEPA training
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