roseking's picture
Add lean source and binary files (part 126)
a2ee19a verified
Raw History Blame Contribute Delete
3.8 kB
import Mathlib
import OAI.Probability.GaussianRegression.Main
import OAI.Probability.MemoryPrecision.RealStream
namespace OAI
open MeasureTheory ProbabilityTheory Set Filter EuclideanGeometry
open scoped ENNReal NNReal RealInnerProductSpace Topology Pointwise
noncomputable section
universe u v
open MeasureTheory ProbabilityTheory Set Filter
open scoped ENNReal NNReal RealInnerProductSpace Topology Pointwise
namespace MemoryPrecision
open NoiselessRegression NoiselessRegression.Learner
lemma estimate_zero {d M : ℕ} {Ω : Type u} (L : Learner d M 0 Ω)
(s : UnitSphere d) (ω : Ω) (x : Samples d 0) :
L.estimate s ω x = L.output 0 ω (L.initialChoice ω).2 := by
by_cases h : (L.initialChoice ω).1 = true <;> simp [estimate, terminal, run, start, h]
lemma frozen_chord_zero {d M : ℕ} {Ω : Type u} (L : Learner d M 0 Ω)
(ω : Ω) (hd : 1 ≤ d) {ε : ℝ} (hε : 0 < ε) :
((uniformSphere d).prod (sampleLaw d 0))
{z | dist z.1.val (L.estimate z.1 ω z.2).val ≤ ε} ≤
ENNReal.ofReal ((3*4^d:ℝ)*ε^(d-1)) := by
let : NeZero d := ⟨by omega⟩
let y := (L.output 0 ω (L.initialChoice ω).2).val
simp_rw [estimate_zero]
change ((uniformSphere d).prod (sampleLaw d 0))
(Prod.fst ⁻¹' {s : UnitSphere d | dist s.val y ≤ ε}) ≤ _
rw [measurePreserving_fst.measure_preimage
(measurableSet_le (measurable_subtype_coe.dist measurable_const) measurable_const).nullMeasurableSet]
have h := ambientSphereLaw_closedBall (E := Space d) y hε (d-1) (by simp)
rw [ambientSphereLaw, Measure.map_apply measurable_subtype_coe Metric.isClosed_closedBall.measurableSet] at h
simpa [uniformSphere, sphereLaw, ENNReal.ofReal_mul, finrank_euclideanSpace_fin,
Metric.closedBall, Set.preimage_ofPred_eq] using h
lemma chord_zero_bound {d M : ℕ} {Ω : Type u} [MeasurableSpace Ω]
(L : Learner d M 0 Ω) (ρ : Measure Ω) [IsProbabilityMeasure ρ]
(hL : L.Admissible ρ) (hd : 1 ≤ d) {ε : ℝ} (hε : 0 < ε) :
uniformChordSuccess L ρ ε ≤ ENNReal.ofReal ((3*4^d:ℝ)*ε^(d-1)) := by
let : NeZero d := ⟨by omega⟩
have hp := ((MeasurePreserving.id (uniformSphere d)).prod
(Measure.measurePreserving_swap (μ := sampleLaw d 0) (ν := ρ))).comp
(measurePreserving_prodAssoc (uniformSphere d) (sampleLaw d 0) ρ)
let S := {z : UnitSphere d × (Ω × Samples d 0) |
dist (L.estimate z.1 z.2.1 z.2.2).val z.1.val ≤ ε}
have hS : NullMeasurableSet S ((uniformSphere d).prod (ρ.prod (sampleLaw d 0))) :=
nullMeasurableSet_le
((measurable_subtype_coe.comp_aemeasurable hL.uniform_experiment).dist
(measurable_subtype_coe.comp measurable_fst).aemeasurable) aemeasurable_const
have he := hp.measure_preimage hS
have hb := prod_null_set_bound (hS.preimage hp.quasiMeasurePreserving)
(c := ENNReal.ofReal ((3*4^d:ℝ)*ε^(d-1)))
(by
filter_upwards [] with ω
change ((uniformSphere d).prod (sampleLaw d 0))
{z | dist (L.estimate z.1 ω z.2).val z.1.val ≤ ε} ≤ _
simpa only [dist_comm] using frozen_chord_zero L ω hd hε)
simpa only [he, measure_univ, mul_one, S, uniformChordSuccess] using hb
lemma angular_event_subset_chord {d M T : ℕ} {Ω : Type u} (L : Learner d M T Ω) (ε : ℝ) :
{z : UnitSphere d × (Ω × Samples d T) |
angularError z.1 (L.estimate z.1 z.2.1 z.2.2) ≤ ε} ⊆
{z | dist (L.estimate z.1 z.2.1 z.2.2).val z.1.val ≤ ε} := by
intro z hz
exact le_trans (chord_le_arccos (L.estimate z.1 z.2.1 z.2.2) z.1) hz
lemma angular_le_chord {d M T : ℕ} {Ω : Type u} [MeasurableSpace Ω]
(L : Learner d M T Ω) (ρ : Measure Ω) (ε : ℝ) :
L.uniformSuccess ρ ε ≤ uniformChordSuccess L ρ ε :=
measure_mono (angular_event_subset_chord L ε)
end MemoryPrecision
end
end OAI