import Mathlib import OAI.Computability.MinUncut.Games.OuterQuestions namespace OAI namespace MinUncutGames.Foundations.Games.FiniteDistribution open scoped BigOperators noncomputable section theorem iid_pushforward {Ω Γ : Type*} [Fintype Ω] [Fintype Γ] (μ : FiniteDistribution Ω) (f : Ω → Γ) (n : Nat) : (μ.pushforward f).iid n = (μ.iid n).pushforward (fun answers i => f (answers i)) := by classical apply eq_of_weight_eq intro y simp only [iid, pushforward] rw [Fintype.prod_sum] apply Finset.sum_congr rfl intro x _ by_cases h : (fun i => f (x i)) = y · have hp : ∀ i, f (x i) = y i := congrFun h simp [hp] · rw [ite_eq_right h] have hn : ¬ ∀ i, f (x i) = y i := fun hp => h (funext hp) obtain ⟨i, hi⟩ := not_forall.mp hn apply Finset.prod_eq_zero (Finset.mem_univ i) simp [hi] def uniform (Ω : Type*) [Fintype Ω] [Nonempty Ω] : FiniteDistribution Ω where weight _ := 1 / (Fintype.card Ω : ℝ) nonnegative _ := div_nonneg zero_le_one (Nat.cast_nonneg _) normalized := by have hn : (Fintype.card Ω : ℝ) ≠ 0 := Nat.cast_ne_zero.mpr Fintype.card_ne_zero simp only [Finset.sum_const, Finset.card_univ, nsmul_eq_mul, one_div] exact mul_inv_cancel₀ hn theorem iid_uniform {Ω : Type*} [Fintype Ω] [Nonempty Ω] (n : Nat) : (uniform Ω).iid n = uniform (Fin n → Ω) := by classical apply eq_of_weight_eq intro x simp [iid, uniform, Nat.cast_pow, one_div] theorem expectation_uniform {Ω : Type*} [Fintype Ω] [Nonempty Ω] (f : Ω → ℝ) : (uniform Ω).expectation f = (∑ x, f x) / (Fintype.card Ω : ℝ) := by unfold expectation uniform rw [← Finset.mul_sum] simp [div_eq_mul_inv, mul_comm] end end MinUncutGames.Foundations.Games.FiniteDistribution noncomputable section open scoped BigOperators namespace MinUncut.Outer open MinUncut.Inner MinUncutGames.Foundations.Games attribute [local instance] Classical.propDecidable variable {Name S : Type*} instance equationFintype [Fintype Name] : Fintype (Equation Name) := Fintype.ofEquiv ((Fin 3 → Name) × F₂) { toFun := fun x => ⟨x.1,x.2⟩ invFun := fun E => (E.names,E.rhs) left_inv := fun _ => rfl right_inv := fun _ => rfl } def ordinaryAccepts (E : Equation Name) (x : Name) (a : Triple) (b : F₂) : Bool := decide (Valid E a ∧ ∀ p, E.names p=x → a p=b) lemma ordinary_all_implies_satisfied (E : Equation Name) (a : Triple) (s : Name → F₂) (h : ∀ p, ordinaryAccepts E (E.names p) a (s (E.names p))=true) : Satisfied s E := by have hvalid : Valid E a := (of_decide_eq_true (h 0)).1 have he : a=evaluatedTriple s E := by funext p exact (of_decide_eq_true (h p)).2 p rfl simpa only [Satisfied,← he] using hvalid.1 lemma ordinary_coordinate_bound (E : Equation Name) (a : Triple) (s : Name → F₂) : (∑ p : Fin 3, if ordinaryAccepts E (E.names p) a (s (E.names p)) then (1 : ℝ) else 0) ≤ 2+(if Satisfied s E then (1 : ℝ) else 0) := by have hall := ordinary_all_implies_satisfied E a s simp only [Fin.sum_univ_three] by_cases h0 : ordinaryAccepts E (E.names 0) a (s (E.names 0))=true <;> by_cases h1 : ordinaryAccepts E (E.names 1) a (s (E.names 1))=true <;> by_cases h2 : ordinaryAccepts E (E.names 2) a (s (E.names 2))=true · have hs : Satisfied s E := hall (by intro p; fin_cases p <;> assumption) norm_num [h0,h1,h2,hs] all_goals simp only [h0,h1,h2,Bool.false_eq_true,↓reduceIte]; split <;> norm_num variable [Fintype S] [Nonempty S] def equationFraction (equations : S → Equation Name) (s : Name → F₂) : ℝ := (∑ i, if Satisfied s (equations i) then (1 : ℝ) else 0)/(Fintype.card S : ℝ) variable [Fintype Name] def ordinaryGame (equations : S → Equation Name) : Game (Equation Name) Name Triple F₂ where questions := (FiniteDistribution.uniform (S × Fin 3)).pushforward (fun ip => (equations ip.1,(equations ip.1).names ip.2)) accepts := ordinaryAccepts lemma ordinary_success_formula (equations : S → Equation Name) (strategy : Strategy (Equation Name) Name Triple F₂) : (ordinaryGame equations).success strategy = (∑ i, ∑ p : Fin 3, if ordinaryAccepts (equations i) ((equations i).names p) (strategy.1 (equations i)) (strategy.2 ((equations i).names p)) then (1 : ℝ) else 0) / ((Fintype.card S : ℝ)*3) := by unfold Game.success dsimp only [ordinaryGame] rw [FiniteDistribution.probability_pushforward] simp only [FiniteDistribution.probability,FiniteDistribution.uniform,Game.wins, Fintype.card_prod,Fintype.card_fin,Nat.cast_mul,Nat.cast_ofNat] rw [Fintype.sum_prod_type] simp only [Finset.sum_div,ite_div,zero_div] lemma ordinary_success_le (equations : S → Equation Name) (strategy : Strategy (Equation Name) Name Triple F₂) : (ordinaryGame equations).success strategy ≤ (2+equationFraction equations strategy.2)/3 := by have hc : (0 : ℝ) ordinary_coordinate_bound (equations i) (strategy.1 (equations i)) strategy.2) simp only [Finset.sum_add_distrib,Finset.sum_const,Finset.card_univ,nsmul_eq_mul] at hsum unfold equationFraction apply (div_le_iff₀ (mul_pos hc (by norm_num : (0 : ℝ)<3))).2 calc _ ≤ (Fintype.card S : ℝ)*2 + ∑ i, if Satisfied strategy.2 (equations i) then (1 : ℝ) else 0 := hsum _ = _ := by field_simp theorem ordinary_value_le (equations : S → Equation Name) (hsound : ∀ s : Name → F₂, equationFraction equations s ≤ 3/4) : (ordinaryGame equations).value ≤ 11/12 := by apply (Game.value_le_iff _ _).2 intro strategy have h := ordinary_success_le equations strategy have hs := hsound strategy.2 linarith end MinUncut.Outer end namespace MinUncutGames.Foundations.Information open scoped BigOperators variable {α : Type*} [Fintype α] def IsProbability (p : α → ℝ) : Prop := (∀ a, 0 ≤ p a) ∧ ∑ a, p a = 1 def SupportedBy (p q : α → ℝ) : Prop := ∀ a, p a ≠ 0 → q a ≠ 0 noncomputable def relativeEntropy (p q : α → ℝ) : ℝ := ∑ a, p a * Real.log (p a / q a) noncomputable def totalVariation (p q : α → ℝ) : ℝ := (∑ a, |p a - q a|) / 2 noncomputable def posterior (p w : α → ℝ) (z : ℝ) : α → ℝ := fun a => p a * w a / z theorem posterior_isProbability (p w : α → ℝ) (hp : IsProbability p) (hw : ∀ a, 0 ≤ w a) {z : ℝ} (hz : 0 < z) (hmass : ∑ a, p a * w a = z) : IsProbability (posterior p w z) := by constructor · intro a exact div_nonneg (mul_nonneg (hp.1 a) (hw a)) hz.le · simp only [posterior, div_eq_mul_inv, ← Finset.sum_mul, hmass, mul_inv_cancel₀ hz.ne'] omit [Fintype α] in theorem posterior_supportedBy (p w : α → ℝ) (z : ℝ) : SupportedBy (posterior p w z) p := by intro a ha hp exact ha (by simp [posterior, hp]) theorem mul_log_div_ge_sub {x y : ℝ} (hx : 0 < x) (hy : 0 < y) : x - y ≤ x * Real.log (x / y) := by have h := Real.one_sub_inv_le_log_of_pos (div_pos hx hy) have hm := mul_le_mul_of_nonneg_left h hx.le have he : x * (1 - (x / y)⁻¹) = x - y := by field_simp [hx.ne', hy.ne'] rwa [he] at hm theorem relativeEntropy_nonneg (p q : α → ℝ) (hp : IsProbability p) (hq : IsProbability q) (hs : SupportedBy p q) : 0 ≤ relativeEntropy p q := by have hpoint : ∀ a, p a - q a ≤ p a * Real.log (p a / q a) := by intro a by_cases hpa : p a = 0 · simp only [hpa, zero_sub, zero_div, zero_mul] exact neg_nonpos.mpr (hq.1 a) · exact mul_log_div_ge_sub (lt_of_le_of_ne (hp.1 a) (Ne.symm hpa)) (lt_of_le_of_ne (hq.1 a) (Ne.symm (hs a hpa))) have hsum := Finset.sum_le_sum (fun a (_ : a ∈ (Finset.univ : Finset α)) => hpoint a) simpa [relativeEntropy, Finset.sum_sub_distrib, hp.2, hq.2] using hsum theorem posterior_relativeEntropy_le (p w : α → ℝ) (hp : IsProbability p) (hw : ∀ a, 0 ≤ w a) (hw_one : ∀ a, w a ≤ 1) {z : ℝ} (hz : 0 < z) (hmass : ∑ a, p a * w a = z) : relativeEntropy (posterior p w z) p ≤ Real.log (1 / z) := by have hpost := posterior_isProbability p w hp hw hz hmass have hpoint : ∀ a, posterior p w z a * Real.log (posterior p w z a / p a) ≤ posterior p w z a * Real.log (1 / z) := by intro a by_cases hpa : posterior p w z a = 0 · simp [hpa] have hpne := posterior_supportedBy p w z a hpa have hppos : 0 < p a := lt_of_le_of_ne (hp.1 a) (Ne.symm hpne) have hpostpos : 0 < posterior p w z a := lt_of_le_of_ne (hpost.1 a) (Ne.symm hpa) have hr : posterior p w z a / p a = w a / z := by dsimp [posterior] field_simp [hpne, hz.ne'] apply mul_le_mul_of_nonneg_left _ (hpost.1 a) apply Real.log_le_log (div_pos hpostpos hppos) rw [hr] exact div_le_div_of_nonneg_right (hw_one a) hz.le have hsum := Finset.sum_le_sum (fun a (_ : a ∈ (Finset.univ : Finset α)) => hpoint a) simpa only [relativeEntropy, ← Finset.sum_mul, hpost.2, one_mul] using hsum theorem totalVariation_nonneg (p q : α → ℝ) : 0 ≤ totalVariation p q := by exact div_nonneg (Finset.sum_nonneg (fun a _ => abs_nonneg (p a - q a))) (by norm_num) theorem totalVariation_symm (p q : α → ℝ) : totalVariation p q = totalVariation q p := by simp only [totalVariation, abs_sub_comm] theorem totalVariation_le_one (p q : α → ℝ) (hp : IsProbability p) (hq : IsProbability q) : totalVariation p q ≤ 1 := by have hpoint : ∀ a, |p a - q a| ≤ p a + q a := by intro a rw [abs_le] constructor <;> linarith [hp.1 a, hq.1 a] have hsum := Finset.sum_le_sum (fun a (_ : a ∈ (Finset.univ : Finset α)) => hpoint a) simp only [Finset.sum_add_distrib, hp.2, hq.2] at hsum dsimp [totalVariation] linarith theorem le_binaryLog_of_le_log {r x : ℝ} (hr : 0 ≤ r) (h : r ≤ Real.log x) : r ≤ Real.log x / Real.log 2 := by have htwo : 0 < Real.log 2 := Real.log_pos (by norm_num) have htwo_one : Real.log 2 ≤ 1 := by have ht := Real.log_le_sub_one_of_pos (show (0 : ℝ) < 2 by norm_num) norm_num at ht ⊢ exact ht apply (le_div_iff₀ htwo).2 exact (mul_le_mul_of_nonneg_left htwo_one hr).trans (by simpa using h) theorem weighted_sum_sq_le (w x : α → ℝ) (hw : IsProbability w) : (∑ a, w a * x a)^2 ≤ ∑ a, w a * (x a)^2 := by have hcs := Finset.sum_mul_sq_le_sq_mul_sq (Finset.univ : Finset α) (fun a => Real.sqrt (w a)) (fun a => Real.sqrt (w a) * x a) have hfirst : ∀ a, Real.sqrt (w a) * (Real.sqrt (w a) * x a) = w a * x a := by intro a rw [← mul_assoc, Real.mul_self_sqrt (hw.1 a)] have hsecond : ∀ a, (Real.sqrt (w a) * x a)^2 = w a * (x a)^2 := by intro a rw [mul_pow, Real.sq_sqrt (hw.1 a)] simpa only [hfirst, hsecond, Real.sq_sqrt (hw.1 _), hw.2, one_mul] using hcs open scoped BigOperators variable {α β : Type*} [Fintype α] [Fintype β] noncomputable def firstMarginal (p : α × β → ℝ) (a : α) : ℝ := ∑ b, p (a, b) noncomputable def secondMarginal (p : α × β → ℝ) (b : β) : ℝ := ∑ a, p (a, b) def product (p : α → ℝ) (q : β → ℝ) : α × β → ℝ := fun ab => p ab.1 * q ab.2 theorem firstMarginal_isProbability (p : α × β → ℝ) (hp : IsProbability p) : IsProbability (firstMarginal p) := by constructor · intro a exact Finset.sum_nonneg (fun b _ => hp.1 (a, b)) · simpa only [firstMarginal, Fintype.sum_prod_type] using hp.2 theorem secondMarginal_isProbability (p : α × β → ℝ) (hp : IsProbability p) : IsProbability (secondMarginal p) := by constructor · intro b exact Finset.sum_nonneg (fun a _ => hp.1 (a, b)) · change (∑ b, ∑ a, p (a, b)) = 1 rw [Finset.sum_comm] exact (firstMarginal_isProbability p hp).2 theorem product_isProbability (p : α → ℝ) (q : β → ℝ) (hp : IsProbability p) (hq : IsProbability q) : IsProbability (product p q) := by constructor · intro ab exact mul_nonneg (hp.1 ab.1) (hq.1 ab.2) · simp only [product, Fintype.sum_prod_type, ← Finset.mul_sum, hq.2, mul_one, hp.2] theorem point_le_firstMarginal (p : α × β → ℝ) (hp : IsProbability p) (a : α) (b : β) : p (a, b) ≤ firstMarginal p a := by classical exact Finset.single_le_sum (fun b _ => hp.1 (a, b)) (Finset.mem_univ b) theorem point_le_secondMarginal (p : α × β → ℝ) (hp : IsProbability p) (a : α) (b : β) : p (a, b) ≤ secondMarginal p b := by classical exact Finset.single_le_sum (fun a _ => hp.1 (a, b)) (Finset.mem_univ a) theorem joint_supportedBy_product_marginals (p : α × β → ℝ) (hp : IsProbability p) : SupportedBy p (product (firstMarginal p) (secondMarginal p)) := by intro ab hpne have hpos : 0 < p ab := lt_of_le_of_ne (hp.1 ab) (Ne.symm hpne) exact mul_ne_zero (ne_of_gt (hpos.trans_le (point_le_firstMarginal p hp ab.1 ab.2))) (ne_of_gt (hpos.trans_le (point_le_secondMarginal p hp ab.1 ab.2))) theorem relativeEntropy_product_reference (p : α × β → ℝ) (u : α → ℝ) (v : β → ℝ) (hp : IsProbability p) (hu : IsProbability u) (hv : IsProbability v) (hsu : SupportedBy (firstMarginal p) u) (hsv : SupportedBy (secondMarginal p) v) : relativeEntropy p (product u v) = relativeEntropy p (product (firstMarginal p) (secondMarginal p)) + relativeEntropy (firstMarginal p) u + relativeEntropy (secondMarginal p) v := by have hpoint : ∀ ab : α × β, p ab * Real.log (p ab / product u v ab) = p ab * Real.log (p ab / product (firstMarginal p) (secondMarginal p) ab) + p ab * Real.log (firstMarginal p ab.1 / u ab.1) + p ab * Real.log (secondMarginal p ab.2 / v ab.2) := by intro ab by_cases hzero : p ab = 0 · simp [hzero] have hpos : 0 < p ab := lt_of_le_of_ne (hp.1 ab) (Ne.symm hzero) have hleft := ne_of_gt (hpos.trans_le (point_le_firstMarginal p hp ab.1 ab.2)) have hright := ne_of_gt (hpos.trans_le (point_le_secondMarginal p hp ab.1 ab.2)) have hune := (lt_of_le_of_ne (hu.1 ab.1) (Ne.symm (hsu ab.1 hleft))).ne' have hvne := (lt_of_le_of_ne (hv.1 ab.2) (Ne.symm (hsv ab.2 hright))).ne' simp only [product, Real.log_div hzero (mul_ne_zero hune hvne), Real.log_div hzero (mul_ne_zero hleft hright), Real.log_mul hune hvne, Real.log_mul hleft hright, Real.log_div hleft hune, Real.log_div hright hvne] ring have hleftSum : (∑ ab : α × β, p ab * Real.log (firstMarginal p ab.1 / u ab.1)) = relativeEntropy (firstMarginal p) u := by simp only [Fintype.sum_prod_type, ← Finset.sum_mul, relativeEntropy, firstMarginal] have hrightSum : (∑ ab : α × β, p ab * Real.log (secondMarginal p ab.2 / v ab.2)) = relativeEntropy (secondMarginal p) v := by rw [Fintype.sum_prod_type, Finset.sum_comm] simp only [← Finset.sum_mul, relativeEntropy, secondMarginal] unfold relativeEntropy simp_rw [hpoint] rw [Finset.sum_add_distrib, Finset.sum_add_distrib, hleftSum, hrightSum] rfl theorem marginal_relativeEntropy_sum_le (p : α × β → ℝ) (u : α → ℝ) (v : β → ℝ) (hp : IsProbability p) (hu : IsProbability u) (hv : IsProbability v) (hsu : SupportedBy (firstMarginal p) u) (hsv : SupportedBy (secondMarginal p) v) : relativeEntropy (firstMarginal p) u + relativeEntropy (secondMarginal p) v ≤ relativeEntropy p (product u v) := by rw [relativeEntropy_product_reference p u v hp hu hv hsu hsv] have hn := relativeEntropy_nonneg p (product (firstMarginal p) (secondMarginal p)) hp (product_isProbability _ _ (firstMarginal_isProbability p hp) (secondMarginal_isProbability p hp)) (joint_supportedBy_product_marginals p hp) linarith noncomputable def conditionalKernel (p : α × β → ℝ) (fallback : β → ℝ) (a : α) (b : β) : ℝ := by classical exact if firstMarginal p a = 0 then fallback b else p (a, b) / firstMarginal p a theorem conditionalKernel_isProbability (p : α × β → ℝ) (fallback : β → ℝ) (hp : IsProbability p) (hf : IsProbability fallback) (a : α) : IsProbability (conditionalKernel p fallback a) := by classical by_cases hm : firstMarginal p a = 0 · simpa only [IsProbability, conditionalKernel, ite_eq_left hm] using hf · constructor · intro b simp only [conditionalKernel, ite_eq_right hm] exact div_nonneg (hp.1 (a, b)) ((firstMarginal_isProbability p hp).1 a) · simp only [conditionalKernel, ite_eq_right hm, div_eq_mul_inv, ← Finset.sum_mul] change firstMarginal p a * (firstMarginal p a)⁻¹ = 1 exact mul_inv_cancel₀ hm theorem marginal_mul_conditionalKernel (p : α × β → ℝ) (fallback : β → ℝ) (hp : IsProbability p) (a : α) (b : β) : firstMarginal p a * conditionalKernel p fallback a b = p (a, b) := by classical by_cases hm : firstMarginal p a = 0 · have hpoint := point_le_firstMarginal p hp a b rw [hm] at hpoint have hz : p (a, b) = 0 := le_antisymm hpoint (hp.1 (a, b)) simp [conditionalKernel, hm, hz] · simp only [conditionalKernel, ite_eq_right hm] calc firstMarginal p a * (p (a, b) / firstMarginal p a) = p (a, b) * (firstMarginal p a / firstMarginal p a) := by ring _ = p (a, b) := by rw [div_self hm, mul_one] theorem law_of_total_probability (p : α × β → ℝ) (fallback : β → ℝ) (hp : IsProbability p) (b : β) : (∑ a, firstMarginal p a * conditionalKernel p fallback a b) = secondMarginal p b := by simp only [marginal_mul_conditionalKernel p fallback hp, secondMarginal] theorem kernelProduct_isProbability (r : α → ℝ) (k : α → β → ℝ) (hr : IsProbability r) (hk : ∀ a, IsProbability (k a)) : IsProbability (fun ab : α × β => r ab.1 * k ab.1 ab.2) := by constructor · intro ab exact mul_nonneg (hr.1 ab.1) ((hk ab.1).1 ab.2) · simp only [Fintype.sum_prod_type, ← Finset.mul_sum, (hk _).2, mul_one, hr.2] theorem alternativeInput_conditionalProduct_isProbability (p : α × β → ℝ) (fallback : β → ℝ) (r : α → ℝ) (hp : IsProbability p) (hf : IsProbability fallback) (hr : IsProbability r) : IsProbability (fun ab : α × β => r ab.1 * conditionalKernel p fallback ab.1 ab.2) := kernelProduct_isProbability r (conditionalKernel p fallback) hr (conditionalKernel_isProbability p fallback hp hf) theorem totalVariation_joint_common_weights (w : α → ℝ) (p q : α → β → ℝ) (hw : ∀ a, 0 ≤ w a) : totalVariation (fun ab : α × β => w ab.1 * p ab.1 ab.2) (fun ab : α × β => w ab.1 * q ab.1 ab.2) = ∑ a, w a * totalVariation (p a) (q a) := by have hpoint : ∀ a b, |w a * p a b - w a * q a b| = w a * |p a b - q a b| := by intro a b rw [← mul_sub, abs_mul, abs_of_nonneg (hw a)] simp only [totalVariation, Fintype.sum_prod_type, hpoint, ← Finset.mul_sum, div_eq_mul_inv, Finset.sum_mul, mul_assoc] theorem totalVariation_joint_common_kernel (p q : α → ℝ) (k : α → β → ℝ) (hk : ∀ a, IsProbability (k a)) : totalVariation (fun ab : α × β => p ab.1 * k ab.1 ab.2) (fun ab : α × β => q ab.1 * k ab.1 ab.2) = totalVariation p q := by have hpoint : ∀ a b, |p a * k a b - q a * k a b| = |p a - q a| * k a b := by intro a b rw [← sub_mul, abs_mul, abs_of_nonneg ((hk a).1 b)] simp only [totalVariation, Fintype.sum_prod_type, hpoint, ← Finset.mul_sum, (hk _).2, mul_one] theorem totalVariation_condition_le (p q : α → ℝ) (event : α → Prop) [DecidablePred event] {c : ℝ} (hc : 0 < c) : totalVariation (fun a => if event a then p a / c else 0) (fun a => if event a then q a / c else 0) ≤ totalVariation p q / c := by have hpoint : ∀ a, |(if event a then p a / c else 0) - (if event a then q a / c else 0)| ≤ |p a - q a| / c := by intro a by_cases he : event a · simp only [ite_eq_left he, ← sub_div, abs_div, abs_of_pos hc, le_refl] · simp only [ite_eq_right he, sub_self, abs_zero] exact div_nonneg (abs_nonneg _) hc.le have hsum := Finset.sum_le_sum (fun a (_ : a ∈ (Finset.univ : Finset α)) => hpoint a) simp only [div_eq_mul_inv, ← Finset.sum_mul] at hsum have hd := div_le_div_of_nonneg_right hsum (show (0 : ℝ) ≤ 2 by norm_num) have hreorder : ((∑ a, |p a - q a|) * c⁻¹) / 2 = ((∑ a, |p a - q a|) / 2) / c := by ring rw [hreorder] at hd simpa only [totalVariation, div_eq_mul_inv] using hd theorem weighted_coordinate_sum_sq_le (w : α → ℝ) (d : α → β → ℝ) (C : α → ℝ) (hw : IsProbability w) (hbudget : ∀ a, w a * (∑ b, d a b ^ 2) ≤ w a * C a) : (∑ b, ∑ a, w a * d a b)^2 ≤ (Fintype.card β : ℝ) * (∑ a, w a * C a) := by have hv := Finset.sum_le_sum (fun b (_ : b ∈ (Finset.univ : Finset β)) => weighted_sum_sq_le w (fun a => d a b) hw) have he : (∑ b, ∑ a, w a * d a b ^ 2) = ∑ a, w a * (∑ b, d a b ^ 2) := by rw [Finset.sum_comm] simp only [Finset.mul_sum] rw [he] at hv have hb := Finset.sum_le_sum (fun a (_ : a ∈ (Finset.univ : Finset α)) => hbudget a) have hs := hv.trans hb have hcs := Finset.sum_mul_sq_le_sq_mul_sq (Finset.univ : Finset β) (fun b => ∑ a, w a * d a b) (fun _ => (1 : ℝ)) simp only [mul_one, one_pow, Finset.sum_const, Finset.card_univ, nsmul_eq_mul, mul_one] at hcs calc (∑ b, ∑ a, w a * d a b)^2 ≤ (∑ b, (∑ a, w a * d a b)^2) * (Fintype.card β : ℝ) := hcs _ = (Fintype.card β : ℝ) * (∑ b, (∑ a, w a * d a b)^2) := mul_comm _ _ _ ≤ (Fintype.card β : ℝ) * (∑ a, w a * C a) := mul_le_mul_of_nonneg_left hs (Nat.cast_nonneg _) end MinUncutGames.Foundations.Information end OAI