Complexity of inversion of functions on the reals
George Barmpalias, Mingyang Wang, Xiaoyan Zhang
TL;DR
This paper investigates the computational difficulty involved in inverting functions defined on real numbers, considering both deterministic and probabilistic approaches, to understand their complexity.
Contribution
It introduces a framework for analyzing the inversion complexity of partial computable functions on the reals, highlighting differences between deterministic and probabilistic methods.
Findings
Deterministic inversion complexity varies with function class.
Probabilistic methods can reduce inversion complexity in some cases.
New theoretical bounds established for inversion problems.
Abstract
We study the complexity of deterministic and probabilistic inversions of partial computable functions on the reals.
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