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Add lean source and binary files (part 64)
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import Mathlib
import OAI.Computability.VertexCover.Information.Finite
namespace OAI
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namespace UniqueGames.Foundations.Information
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 := hsu ab.1 hleft
have hvne := hsv ab.2 hright
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
end UniqueGames.Foundations.Information
end
end
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end
end OAI