A hybrid evolution-strategy and gradient-descent framework maximizes a non-differentiable 'surprise score' to discover non-random features for non-parametric self-supervised image clustering.
The hungarian method for the as- signment problem.Naval research logistics quarterly, 2(1-2):83–97, 1955
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Converge to Surprise: Evolutionary Self-supervised Image Clustering
A hybrid evolution-strategy and gradient-descent framework maximizes a non-differentiable 'surprise score' to discover non-random features for non-parametric self-supervised image clustering.