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Author

Xiuwen Liu

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Converge to Surprise: Evolutionary Self-supervised Image Clustering

This work proposes the converge-to-surprise scheme to optimize a model: an evolution-strategy (ES) outer loop, which maximizes the surprise score using the mutation-selection mechanism, paired with a periodic gradient-descent inner loop, which uses the surprising clusters already discovered by ES as surrogate targets.

Canlin Zhang, Xiuwen Liu · 0 citations

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