arXiv Machine Learning July 9, 2026 By Canlin Zhang, Xiuwen Liu

Converge to Surprise: Evolutionary Self-supervised Image Clustering

Read the original on arXiv Machine Learning →

arXiv:2607. 06887v1 Announce Type: new Abstract: Most self-supervised image clustering models, actually almost all deep learning approaches, are based on gradient descent: In order to calculate the loss, every optimization step requires a clearly defined target, whether a contrastive split, a masked patch or entity, an EMA-teacher output, a pseudo-label, or a differentiable information-theoretic functional.

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