import OAI.Probability.MatroidProphet.Main import OAI.Probability.MatroidSecretary.Selection.SafeSpecification namespace OAI namespace MatroidProphet open Finset variable {α : Type*} [Fintype α] [DecidableEq α] /-- The stronger half-loss estimate explicitly obtained in the source proof. The named lemma then enlarges the loss from `|D_h|/(2κ)` to `|D_h|/κ`. -/ theorem safeSampleCount_half_loss (M : Matroid α) (hE : M.E = Set.univ) (κ : ℕ) (hκ : 0 < κ) (D : ℕ → Set α) (G : ℕ → Finset α) (hG : Pairwise (fun i j => Disjoint (G i) (G j))) (q : α → ℝ) (hq0 : ∀ e, 0 ≤ q e) (hq1 : ∀ e, q e ≤ 1) (h : ℕ) (I : Finset α) (hI : M.Indep (I : Set α)) : (((2 : ℝ) ^ 12)⁻¹) / 4 * I.card - (D h).ncard / (2 * (κ : ℝ)) ≤ bitsExpectation q univ (fun C => bitsExpectation q univ (fun T => fairParityExpectation (safeSampleCount M hE κ D G h I C T))) := by have hpre := safeCountBeforeParity_lower M hE κ hκ D G hG q hq0 hq1 h I hI have heq : bitsExpectation q univ (fun C => bitsExpectation q univ (fun T => fairParityExpectation (safeSampleCount M hE κ D G h I C T))) = bitsExpectation q univ (fun C => bitsExpectation q univ (safeCountBeforeParity M hE κ D G h I C)) / 2 := by simp only [safeSampleCount_fair_parity, div_eq_mul_inv] simp_rw [bitsExpectation_mul_right] rw [heq] have hloss : ((D h).ncard : ℝ) / (2 * (κ : ℝ)) = ((D h).ncard : ℝ) / (κ : ℝ) / 2 := by ring rw [hloss] linarith end MatroidProphet namespace MatroidProphet.MainAlgorithm open Finset variable {n : ℕ} attribute [local instance] Classical.propDecidable /-- The fixed-density safety estimate with the exact density-sample loss. -/ theorem listedSafeStatistic_exact_density (M : Matroid (Fin n)) (hE : M.E = Set.univ) (κ : ℕ) (hκ : 0 < κ) (d : MainMasks n) (s : Fin n → Option ℤ) (i : ℤ) (Y : Set (Fin n)) (hY : Y ⊆ (trueGroup M d s i : Set (Fin n))) (hI : M.Indep Y) (q : Fin n → ℝ) (hq0 : ∀ e, 0 ≤ q e) (hq1 : ∀ e, q e ≤ 1) : exitThreshold / 4 * ((d.D : Set (Fin n)) ∩ Y).ncard - (d.D ∩ trueGroup M d s i).card / (κ : ℝ) ≤ bitsExpectation q univ (fun C => bitsExpectation q univ (fun T => fairParityExpectation (fun p => (listedSafeStatistic M hE κ (withMasks d d.D C T) s i Y (boolParity p) : ℝ)))) := by by_cases hi : i ∈ groups M d s · have hsafe := safeLayerStatistic_lower M hE κ hκ (groupMask M d s d.D) (groupGround M d s) (groupGround_disjoint M d s) q hq0 hq1 ((groups M d s).idxOf i) (trueGroup M d s i : Set (Fin n)) ((d.D : Set (Fin n)) ∩ Y) (Set.inter_subset_right.trans hY) (hI.subset Set.inter_subset_right) rw [groupMask_at_key M d s d.D _ i (groups_get?_idxOf M d s i hi), Set.ncard_coe_finset] at hsafe simpa only [listedSafeStatistic_guards M hE κ d s i Y, hi, exitThreshold] using hsafe · have hempty := unlisted_density_inter_empty M d s i hi Y hY have hzero (C T : Finset (Fin n)) (p : Bool) : listedSafeStatistic M hE κ (withMasks d d.D C T) s i Y (boolParity p) = 0 := by change (if i ∈ groups M d s then _ else 0) = 0 rw [ite_eq_right hi] simp only [hempty, Set.ncard_empty, Nat.cast_zero, mul_zero, zero_sub, hzero, fairParityExpectation, zero_add, zero_div, bitsExpectation_const] exact neg_nonpos.mpr (div_nonneg (Nat.cast_nonneg _) (Nat.cast_nonneg _)) /-- Restricting the comparison set to this true group does not change its safe-label statistic. This permits the source's global independent set `Y`. -/ theorem listedSafeStatistic_inter_trueGroup (M : Matroid (Fin n)) (hE : M.E = Set.univ) (κ : ℕ) (d : MainMasks n) (s : Fin n → Option ℤ) (i : ℤ) (Y : Set (Fin n)) (ε : Fin 2) : listedSafeStatistic M hE κ d s i (Y ∩ (trueGroup M d s i : Set (Fin n))) ε = listedSafeStatistic M hE κ d s i Y ε := by unfold listedSafeStatistic split_ifs · unfold safeLayerStatistic apply sum_congr rfl intro b _ congr 1 ext e simp only [safeLayerSet, Set.mem_sdiff, Set.mem_inter_iff] constructor · rintro ⟨⟨⟨heD, heY, _⟩, heL⟩, heN⟩ exact ⟨⟨⟨heD, heY⟩, heL⟩, heN⟩ · rintro ⟨⟨⟨heD, heY⟩, heL⟩, heN⟩ exact ⟨⟨⟨heD, heY, heL.1⟩, heL⟩, heN⟩ · rfl /-- Source `lem:safe`, specialized to the manuscript's literal density threshold and thinning rate, for the global independent comparison set. It also covers an unlisted group, whose safe count is defined to be zero. -/ theorem safe_sampled_labels (M : Matroid (Fin n)) (hE : M.E = Set.univ) (d : MainMasks n) (s : Fin n → Option ℤ) (i : ℤ) (Y : Set (Fin n)) (hI : M.Indep Y) : exitThreshold / 4 * ((d.D : Set (Fin n)) ∩ (Y ∩ (trueGroup M d s i : Set (Fin n)))).ncard - (d.D ∩ trueGroup M d s i).card / densityThreshold ≤ bitsExpectation (fun _ => thinningRate) univ (fun C => bitsExpectation (fun _ => thinningRate) univ (fun T => fairParityExpectation (fun p => (listedSafeStatistic M hE (2 ^ 100) (withMasks d d.D C T) s i Y (boolParity p) : ℝ)))) := by have hs := listedSafeStatistic_exact_density M hE (2 ^ 100) (by positivity) d s i (Y ∩ (trueGroup M d s i : Set (Fin n))) Set.inter_subset_right (hI.subset Set.inter_subset_left) (fun _ => thinningRate) (fun _ => constants_positive.2.2.1.le) (fun _ => by norm_num [thinningRate]) have heq (C T : Finset (Fin n)) (p : Bool) : listedSafeStatistic M hE (2 ^ 100) (withMasks d d.D C T) s i (Y ∩ (trueGroup M d s i : Set (Fin n))) (boolParity p) = listedSafeStatistic M hE (2 ^ 100) (withMasks d d.D C T) s i Y (boolParity p) := by simpa only [trueGroup_withMasks] using listedSafeStatistic_inter_trueGroup M hE (2 ^ 100) (withMasks d d.D C T) s i Y (boolParity p) simpa only [Nat.cast_pow, Nat.cast_ofNat, densityThreshold, heq] using hs /-- Proof of the independently stated complete safe-label claim. -/ theorem safe_sampled_labels_claim : SafeSampleClaim := by intro n M hE d s i Y hI exact safe_sampled_labels M hE d s i Y hI end MatroidProphet.MainAlgorithm end OAI