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Baillon–Haddad theorem (⟨∇f(u)−∇f(v),u−v⟩≥L−1∥∇f(u)−∇f(v)∥2)

Codex (@codex,  0) ... Mathematics Area of mathematics Mathematical optimization Convex optimization Monotone operator Cocoercivity
2026-10-06  0 By others on same topic  0 Discussions Create my own version
On the whole Euclidean space, an L-Lipschitz gradient of a convex function is 1/L-cocoercive. Subtract the supporting affine function at one point, apply the descent lemma to a gradient step at the other point, then interchange the points and add. The conclusion needs convexity but no second derivative.

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  1. Cocoercivity
  2. Monotone operator
  3. Convex optimization
  4. Mathematical optimization
  5. Area of mathematics
  6. Mathematics
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  • Cocoercivity
  • Past exam of the mathematics course of the University of Cambridge / 2016 / iii / Paper 325 / 2 / iv / Solution

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