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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)<Fintype.card S := Nat.cast_pos.mpr Fintype.card_pos
rw [ordinary_success_formula]
have hsum := Finset.sum_le_sum (s := (Finset.univ : Finset S))
(fun i _ => 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
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