Dimension-independent bounds for tuple averaging
Lax253009.TupleAveraging · concepts/Lax253009/TupleAveraging.lean · lax-253009
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Theorem
The average of t independent samples of a function in [-1,1] has variance at most 1/t. Restricting to any event cannot increase its unnormalized correlation with the centered sample average beyond 1/sqrt(t). These bounds do not depend on the size of the sample alphabet. They provide the averaging estimate for fortifying projection games by tuple questions.
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| 1 | import Lax253009.FiniteProbability |
| 2 | import Mathlib.Data.Fintype.Pi |
| 3 | |
| 4 | /-! |
| 5 | --- |
| 6 | title: Dimension-independent bounds for tuple averaging |
| 7 | type: theorem |
| 8 | --- |
| 9 | The average of t independent samples of a function in [-1,1] has variance |
| 10 | at most 1/t. Restricting to any event cannot increase its unnormalized |
| 11 | correlation with the centered sample average beyond 1/sqrt(t). |
| 12 | These bounds do not depend on the size of the sample alphabet. They provide |
| 13 | the averaging estimate for fortifying projection games by tuple questions. |
| 14 | -/ |
| 15 | |
| 16 | namespace Lax253009.TupleAveraging |
| 17 | |
| 18 | open scoped BigOperators |
| 19 | |
| 20 | axiom variance_bound {A : Type} [Fintype A] [Nonempty A] |
| 21 | (t : ℕ) (ht : 0 < t) (f : A → ℝ) (hf : ∀ a, |f a| ≤ 1) : |
| 22 | (𝔼 z : Fin t → A, ((𝔼 i, f (z i)) - (𝔼 a, f a)) ^ 2) ≤ 1 / (t : ℝ) |
| 23 | |
| 24 | axiom restriction_correlation {A : Type} [Fintype A] [Nonempty A] |
| 25 | (t : ℕ) (ht : 0 < t) (f : A → ℝ) (hf : ∀ a, |f a| ≤ 1) |
| 26 | (S : (Fin t → A) → Prop) [DecidablePred S] : |
| 27 | |𝔼 z : Fin t → A, if S z then (𝔼 i, f (z i)) - (𝔼 a, f a) else 0| ^ 2 ≤ |
| 28 | 1 / (t : ℝ) |
| 29 | |
| 30 | end Lax253009.TupleAveraging |
| 31 |
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