New Insight of Variance reduce in Zero-Order Hard-Thresholding: Mitigating Gradient Error and Expansivity Contradictions

In three linesNew zeroth-order hard-thresholding algorithm with variance reduction for ℓ0-constrained optimization. Addresses SZOHT's limitation on random directions by mitigating conflict between ZO gradient deviation and hard-thresholding expansivity. Improved convergence rates validated on ridge regression and black-box adversarial attacks.

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