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import OAI.Probability.SKRatio.FiniteChain.WeightedKernelOperator
import OAI.Probability.SKRatio.Variational.FormContinuity
import OAI.Probability.SKRatio.Matrices.AugmentedBounds
namespace OAI
noncomputable section
open scoped BigOperators NNReal ENNReal Topology
open MeasureTheory ProbabilityTheory Filter Set Real
namespace SKRatio.Planted
open SKRatioClock.Regression MatrixNet Calculus Scalar
attribute [local instance] Classical.propDecidable
variable {n : ℕ}
lemma weighted_operator_event_measurable {X : Type*} (β u : ℝ) (G : X × X → ℝ) :
MeasurableSet {g : Disorder n | ∃ x : Fin n → X,
u < euclideanOpNorm (fun i j => squareError β g i j*G (x i,x j))} := by
let : ContinuousSMul ℝ (EuclideanSpace ℝ (Fin n)) := IsBoundedSMul.continuousSMul
let : ContinuousSMul ℝ (EuclideanSpace ℝ (Fin n) →L[ℝ] EuclideanSpace ℝ (Fin n)) :=
ContinuousLinearMap.continuousSMul
simp only [ofPred_exists]
apply IsOpen.measurableSet
apply isOpen_iUnion
intro x
apply isOpen_lt continuous_const
apply continuous_norm.comp
apply ((Matrix.toEuclideanCLM (𝕜 := ℝ) (n := Fin n)).toAlgEquiv.toLinearEquiv.toLinearMap.continuous_of_finiteDimensional).comp
apply continuous_pi
intro i
apply continuous_pi
intro j
exact (((continuous_coupling i j).pow 2).sub continuous_const).mul_const _
lemma augmented_weighted_operator_rare {X : Type*} [PseudoMetricSpace X] [CompactSpace X]
(β : ℝ) (G : X × X → ℝ) (hG : Continuous G) {u : ℝ} (hu : 0<u) :
ExponentiallyRare (fun n => standardArrayLaw (Fin n × Fin n))
(fun n => {g | ∃ x : Fin n → X, u < euclideanOpNorm
(fun i j => squareError β (augmentedDisorder β g) i j*G (x i,x j))}) := by
obtain ⟨C,c,hC,hc,ht⟩ := weighted_square_operator_rare β G hG hu
refine ⟨C,c,hC,hc,?_⟩
filter_upwards [ht,eventually_gt_atTop 0] with n hn hn0
rw [(augmentedDisorder_hasLaw hn0 β).measure_eq (weighted_operator_event_measurable β u G)]
exact hn
lemma squareError_row (β : ℝ) (g : Disorder n) (f : Fin n → ℝ) (i : Fin n) :
(∑ j, squareError β g i j*f j) =
(∑ e : incidentEdges i, (g e^2-β^2/(n:ℝ))*f (otherEnd i e))-β^2/(n:ℝ)*f i := by
have he := squareError_decomposition β g
simp_rw [show (fun i j => squareError β g i j)=
(fun i j => coupling (fun e => g e^2-β^2/(n:ℝ)) i j-
Matrix.diagonal (fun _ => β^2/(n:ℝ)) i j) from congrArg (fun m => fun i j => m i j) he]
simp only [sub_mul,Finset.sum_sub_distrib]
rw [sum_coupling_weighted_row]
simp only [←Finset.sum_attach (s := incidentEdges i)]
congr 1
· simp only [sub_mul,Finset.sum_sub_distrib, Finset.attach_eq_univ]
· simp [Matrix.diagonal_apply,ite_mul]
lemma diagonal_weight_bound (G : FieldWeight × FieldWeight → ℝ) (x : Fin n → FieldWeight)
(p ζ : Fin n → ℝ) {u : ℝ} (hζ : ∀ i, |ζ i| ≤ u)
(hG : ∀ a : FieldWeight, |G (a,a)| ≤ 1) :
|weightedForm (Matrix.diagonal ζ) G x p| ≤ u*∑ i, p i^2 := by
have hf : weightedForm (Matrix.diagonal ζ) G x p = ∑ i, ζ i*G (x i,x i)*p i^2 := by
simp only [weightedForm,quadratic,Matrix.diagonal_apply,ite_mul,zero_mul,
Finset.sum_ite_eq,Finset.mem_univ,ite_true]
apply Finset.sum_congr rfl
intro i _
ring
rw [hf]
apply (Finset.abs_sum_le_sum_abs _ _).trans
calc
_ ≤ ∑ i, u*p i^2 := Finset.sum_le_sum (fun i _ => by
rw [abs_mul,abs_mul,abs_of_nonneg (sq_nonneg (p i))]
exact mul_le_mul_of_nonneg_right
((mul_le_mul_of_nonneg_left (hG (x i)) (abs_nonneg _)).trans (by simpa only [mul_one] using hζ i))
(sq_nonneg _))
_ = _ := (Finset.mul_sum ..).symm
lemma compactF_le_eight (a b : FieldWeight) : |compactF (a,b)|≤8 := by
rw [abs_of_nonneg (compactF_nonneg _)]
exact (compactF_bound _).trans (by nlinarith [b.2.2])
def reducedForm (β : ℝ) (g : (Fin n × Fin n) → ℝ) (p : Fin n → ℝ) : ℝ :=
let x := fun i => compactWeight (augmentedField β g i)
weightedForm (augmented β g) varianceKernel x p +
2*weightedForm (fun _ _ => β^2/(n:ℝ)) meanVarianceKernel x p +
diagonalForm (fun _ _ => β^2/(n:ℝ)) compactF x p +
weightedForm (fun _ _ => β^2/(n:ℝ)) compactK x p
lemma compactForm_reduced_error (β : ℝ) (g : (Fin n × Fin n) → ℝ)
(p : Fin n → ℝ) {a d : ℝ}
(hdiag : ∀ i, |augmentedDiagonal β g i|≤a)
(hm : ∀ x : Fin n → FieldWeight, euclideanOpNorm
(fun i j => squareError β (augmentedDisorder β g) i j*meanVarianceKernel (x i,x j)) ≤ a)
(hk : ∀ x : Fin n → FieldWeight, euclideanOpNorm
(fun i j => squareError β (augmentedDisorder β g) i j*compactK (x i,x j)) ≤ a)
(hf : ∀ i, |∑ e : incidentEdges i, (augmentedDisorder β g e^2-β^2/(n:ℝ))*
compactF (compactWeight (augmentedField β g i),compactWeight (augmentedField β g (otherEnd i e)))| ≤ d) :
|compactForm (coupling (augmentedDisorder β g))
(fun i => compactWeight (augmentedField β g i)) p-reducedForm β g p| ≤
(4*a+d+8*β^2/(n:ℝ))*(∑ i, p i^2) := by
let J := coupling (augmentedDisorder β g)
let x := fun i => compactWeight (augmentedField β g i)
let L := weightedForm J varianceKernel x p-weightedForm (augmented β g) varianceKernel x p
let Q : Matrix (Fin n) (Fin n) ℝ := Matrix.of (fun i j => J i j^2)
let B : Matrix (Fin n) (Fin n) ℝ := Matrix.of (fun _ _ => β^2/(n:ℝ))
let M := weightedForm Q meanVarianceKernel x p-weightedForm B meanVarianceKernel x p
let D := diagonalForm Q compactF x p-diagonalForm B compactF x p
let K := weightedForm Q compactK x p-weightedForm B compactK x p
have hL : |L|≤a*(∑ i, p i^2) := by
have hd := diagonal_weight_bound varianceKernel x p (augmentedDiagonal β g) hdiag
(fun b => by simpa only [varianceKernel,abs_of_nonneg (compactV_nonneg b)] using compactV_le_one b)
have he : weightedForm (augmented β g) varianceKernel x p =
weightedForm J varianceKernel x p+weightedForm (Matrix.diagonal (augmentedDiagonal β g)) varianceKernel x p := by
have hmat : augmented β g = (Matrix.of J)+Matrix.diagonal (augmentedDiagonal β g) := by
dsimp only [J]
rw [coupling_augmentedDisorder]
change augmented β g = (augmented β g - Matrix.diagonal (augmentedDiagonal β g)) + Matrix.diagonal (augmentedDiagonal β g)
exact (sub_add_cancel _ _).symm
rw [hmat]
simp only [weightedForm,quadratic,Matrix.add_apply,add_mul,Finset.sum_add_distrib,Matrix.of_apply]
dsimp [L]
rw [he,sub_add_cancel_left,abs_neg]
exact hd
have hM : |M|≤a*(∑ i, p i^2) := by
dsimp only [M]
rw [weightedForm_sub]
exact (quadratic_abs_le _ p).trans (mul_le_mul_of_nonneg_right (hm x)
(Finset.sum_nonneg (fun _ _ => sq_nonneg _)))
have hK : |K|≤a*(∑ i, p i^2) := by
dsimp only [K]
rw [weightedForm_sub]
exact (quadratic_abs_le _ p).trans (mul_le_mul_of_nonneg_right (hk x)
(Finset.sum_nonneg (fun _ _ => sq_nonneg _)))
have hD : |D|≤(d+8*β^2/(n:ℝ))*(∑ i, p i^2) := by
dsimp only [D]
rw [diagonalForm_sub]
apply diagonalForm_abs_le
intro i
change |∑ j, squareError β (augmentedDisorder β g) i j*compactF (x i,x j)|≤_
rw [squareError_row]
apply (abs_sub _ _).trans
apply add_le_add (hf i)
rw [abs_mul,abs_of_nonneg (by positivity : 0≤β^2/(n:ℝ))]
have hh := mul_le_mul_of_nonneg_left (compactF_le_eight (x i) (x i))
(show 0≤β^2/(n:ℝ) by positivity)
convert hh using 1
ring
have hid : compactForm J x p-reducedForm β g p=L+2*M+D+K := by
dsimp [compactForm,reducedForm,L,M,D,K,x,Q,B]
simp only [weightedForm,diagonalForm,Matrix.of_apply]
ring
change |compactForm J x p-reducedForm β g p| ≤ _
rw [hid]
have ht := (abs_add_le (L+2*M+D) K).trans
(add_le_add ((abs_add_le (L+2*M) D).trans (add_le_add (abs_add_le L (2*M)) le_rfl)) le_rfl)
rw [abs_mul,abs_of_pos (by norm_num : (0:ℝ)<2)] at ht
nlinarith only [ht,hL,hM,hD,hK]
theorem reduced_error_rare {β : ℝ} (hβ : 0<β) {u : ℝ} (hu : 0<u) :
ExponentiallyRare (fun n => standardArrayLaw (Fin n × Fin n))
(fun n => {g | ∃ p : Fin n → ℝ, u*(∑ i, p i^2)<
|gradientForm (coupling (augmentedDisorder β g)) p-reducedForm β g p|}) := by
let K := 2*β+β^2+1
have hK : 0≤K := by dsimp [K]; positivity
let a := u/8
have ha : 0<a := by dsimp [a]; positivity
obtain ⟨δ,hδ,hfield⟩ := compactForm_uniform_field_change (sq_nonneg K) hK ha
have hN := augmented_norm_rare hβ (by norm_num : (0:ℝ)<1)
have hD := augmented_diagonal_rare β (lt_min hδ ha)
have hM := augmented_weighted_operator_rare β meanVarianceKernel continuous_meanVarianceKernel ha
have hC := augmented_weighted_operator_rare β compactK continuous_compactK ha
have hF := augmented_weighted_diagonal_rare compactF continuous_compactF compactWeight compactWeight_lipschitz β ha
apply ((((hN.union hD).union hM).union hC).union hF).mono
have ht : ∀ᶠ n : ℕ in atTop, 8*β^2/(n:ℝ)≤a :=
((tendsto_const_div_atTop_nhds_zero_nat (𝕜 := ℝ) (8*β^2)).eventually (gt_mem_nhds ha)).mono
(fun _ hn => hn.le)
filter_upwards [ht] with n hn
rintro g ⟨p,hp⟩
by_contra hb
have hnorm : euclideanOpNorm (coupling (augmentedDisorder β g))≤K :=
le_of_not_gt (fun h => hb (Or.inl (Or.inl (Or.inl (Or.inl h)))))
have hdiag : ∀ i, |augmentedDiagonal β g i|≤ min δ a :=
fun i => le_of_not_gt (fun h => hb (Or.inl (Or.inl (Or.inl (Or.inr ⟨i,h⟩)))))
have hm : ∀ x : Fin n → FieldWeight, euclideanOpNorm
(fun i j => squareError β (augmentedDisorder β g) i j*meanVarianceKernel (x i,x j))≤a :=
fun x => le_of_not_gt (fun h => hb (Or.inl (Or.inl (Or.inr ⟨x,h⟩))))
have hk : ∀ x : Fin n → FieldWeight, euclideanOpNorm
(fun i j => squareError β (augmentedDisorder β g) i j*compactK (x i,x j))≤a :=
fun x => le_of_not_gt (fun h => hb (Or.inl (Or.inr ⟨x,h⟩)))
have hf : ∀ i, |∑ e : incidentEdges i, (augmentedDisorder β g e^2-β^2/(n:ℝ))*
compactF (compactWeight (augmentedField β g i),compactWeight (augmentedField β g (otherEnd i e)))|≤a :=
fun i => le_of_not_gt (fun h => hb (Or.inr ⟨i,h⟩))
let J := coupling (augmentedDisorder β g)
have hefield (i : Fin n) : |(∑ j, J i j)-augmentedField β g i|≤δ := by
rw [←diagonalField_augmented]
change |(∑ j, J i j)-(augmentedDiagonal β g i+(∑ j, J i j))|≤δ
rw [sub_add_cancel_right,abs_neg]
exact (hdiag i).trans (min_le_left _ _)
have h₁ := hfield J (coupling_symm _) hnorm
(row_squares_le_opNorm J (coupling_symm _) hK hnorm) _ _ p hefield
have h₂ := compactForm_reduced_error β g p (fun i => (hdiag i).trans (min_le_right _ _)) hm hk hf
have hgrad := gradientForm_eq_compactForm J (coupling_symm _) (coupling_diag _) p
rw [hgrad] at hp
have habs := abs_sub_le (compactForm J (fun i => compactWeight (∑ j, J i j)) p)
(compactForm J (fun i => compactWeight (augmentedField β g i)) p) (reducedForm β g p)
have hnorm0 : 0≤∑ i, p i^2 := Finset.sum_nonneg (fun _ _ => sq_nonneg _)
have hh := mul_le_mul_of_nonneg_right hn hnorm0
dsimp [a] at h₁ h₂ hh
nlinarith only [hp,habs,h₁,h₂,hh,hu,hnorm0]
end SKRatio.Planted
end
end OAI
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