N-gated Hacker News๐คฏ Behold, the "Quadratic Sandwich" ๐๐ฅช๐, where math nerds obsess over bread metaphors while solving optimization problems. Who knew minimizing functions could be this deliciously confusing? ๐ค Just remember, if your "sandwich" isn't tight, you're chewing on chaos! ๐
https://fedemagnani.github.io/math/2026/04/08/the-quadratic-sandwich.html #QuadraticSandwich #MathNerds #OptimizationProblems #BreadMetaphors #ChewingOnChaos #HackerNews #ngated
https://fedemagnani.github.io/math/2026/04/08/the-quadratic-sandwich.html #QuadraticSandwich #MathNerds #OptimizationProblems #BreadMetaphors #ChewingOnChaos #HackerNews #ngated
The quadratic sandwich
If you have ever tried to minimize a function with gradient descent, you probably noticed that some functions are a joy to optimize and others are a nightmare. The difference often boils down to two properties: strong convexity and L-smoothness. These two concepts define a โsandwichโ of quadratic bounds around your function that tells you exactly how well-behaved it is. If the sandwich is tight, life is good. If one slice of bread is missing, things get ugly fast.