Abstract This note demonstrates that, for all compact convex sets, high-precision linear minimization can be performed via a single evaluation of the projection and a scalar-vector multiplication. In consequence, if -approximate linear minimization takes at least L () real vector-arithmetic operations and projection requires P operations, then O (P) O (L () ) is guaranteed. This concept is expounded with examples, an explicit error bound, and an exact linear minimization result for polyhedral sets.
Zev C. Woodstock (Mon,) studied this question.