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.
Indicator functions for adaptive image processing.Journal of the Optical So- ciety of America A, 8(1):141–156, 1991
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
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.