Theoremresearch
First-order lower bound for smooth convex optimization
Also called Nesterov lower bound, Nemirovski-Yudin lower bound.
No first-order method can beat an Omega(1/k^2) rate on smooth convex problems, so Nesterov's method is optimal.
No first-order method can beat an Omega(1/k^2) rate on smooth convex problems, so Nesterov's method is optimal.
About this page
The build computes these levels from the evidence in the repository. Each row says what the next level needs. Read what the levels mean.
| Ladder | Level | What the next level needs |
|---|---|---|
| Human proof | H0 no proof |
|
| Lean | L0 no Lean part |
|
| Visual | V0 none |
|
| Writing | W0 stub |
|
Tag 0CXN65 Edit this page History Report an error