Introduces hybrid noise and novel coupling analysis to achieve the first convergent hidden-state DP bound for zeroth-order optimization.
We set the radius of the projected set to be R = 1, smooth constant M = 1, strongly convex constant m = 0.9, and the clipped norm ∆ = 1
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Privacy Amplification in Differentially Private Zeroth-Order Optimization with Hidden States
Introduces hybrid noise and novel coupling analysis to achieve the first convergent hidden-state DP bound for zeroth-order optimization.