Suppose I have an optimization problem of the form $$ \inf_{\{x \in \mathbb{R}^d: g(x)=0\}} f(x), $$ for some convex function $f$ and non-convex l.s.c. function $g$.
Can we reinterpret the Lagrange multiplier $\mu$, as the reciprocal of smallest $\lambda \in [0,1]$ such that the set $$ \operatorname{arginf} \left[ (1-\lambda)f(x) + \lambda g(x) \right] \cap \{ x \in \mathbb{R}^d : g(x)=0 \} \neq \emptyset \text{?} $$
(sort of a first point of contact)