Bandits.prob_sum_le_sqrt_log
No docstring.
Bandits.prob_sum_le_sqrt_log.{u_1} {๐ : Type u_1} {m๐ : MeasurableSpace ๐} {ฮฝ : ProbabilityTheory.Kernel ๐ โ} [ProbabilityTheory.IsMarkovKernel ฮฝ] {n : โ} {ฯ2 : NNReal} (hฮฝ : โ (a : ๐), ProbabilityTheory.HasSubgaussianMGF (fun x => x - โซ (x : โ), id x โฮฝ a) ฯ2 (ฮฝ a)) (hฯ2 : ฯ2 โ 0) {c : โ} (hc : 0 โค c) (a : ๐) (k : โ) (hk : k โ 0) : (streamMeasure ฮฝ) {ฯ | โ s โ Finset.range k, (ฯ s a - โซ (x : โ), id x โฮฝ a) โค -โ(2 * c * โk * โฯ2 * Real.log (โn + 1))} โค 1 / (โn + 1) ^ cBandits.prob_sum_le_sqrt_log.{u_1} {๐ : Type u_1} {m๐ : MeasurableSpace ๐} {ฮฝ : ProbabilityTheory.Kernel ๐ โ} [ProbabilityTheory.IsMarkovKernel ฮฝ] {n : โ} {ฯ2 : NNReal} (hฮฝ : โ (a : ๐), ProbabilityTheory.HasSubgaussianMGF (fun x => x - โซ (x : โ), id x โฮฝ a) ฯ2 (ฮฝ a)) (hฯ2 : ฯ2 โ 0) {c : โ} (hc : 0 โค c) (a : ๐) (k : โ) (hk : k โ 0) : (streamMeasure ฮฝ) {ฯ | โ s โ Finset.range k, (ฯ s a - โซ (x : โ), id x โฮฝ a) โค -โ(2 * c * โk * โฯ2 * Real.log (โn + 1))} โค 1 / (โn + 1) ^ c
Code
lemma prob_sum_le_sqrt_log {ฯ2 : โโฅ0}
(hฮฝ : โ a, HasSubgaussianMGF (fun x โฆ x - (ฮฝ a)[id]) ฯ2 (ฮฝ a))
(hฯ2 : ฯ2 โ 0) {c : โ} (hc : 0 โค c) (a : ๐) (k : โ) (hk : k โ 0) :
streamMeasure ฮฝ
{ฯ | (โ s โ range k, (ฯ s a - (ฮฝ a)[id])) โค - โ(2 * c * k * ฯ2 * Real.log (n + 1))} โค
1 / (n + 1) ^ cProof
by
calc
streamMeasure ฮฝ
{ฯ | (โ s โ range k, (ฯ s a - (ฮฝ a)[id])) โค - โ(2 * c * k * ฯ2 * Real.log (n + 1))}
_ โค ENNReal.ofReal (Real.exp (-(โ(2 * c * k * ฯ2 * Real.log (n + 1))) ^ 2 / (2 * k * ฯ2))) := by
rw [โ ofReal_measureReal]
gcongr
refine (HasSubgaussianMGF.measure_sum_range_le_le_of_iIndepFun (c := ฯ2) ?_ ?_ (by positivity))
ยท exact (iIndepFun_eval_streamMeasure'' ฮฝ a).comp (fun i ฯ โฆ ฯ - (ฮฝ a)[id])
(fun _ โฆ by fun_prop)
ยท intro i him
refine (hฮฝ a).congr_identDistrib ?_
exact (identDistrib_eval_eval_id_streamMeasure _ _ _).symm.sub_const _
_ = 1 / (n + 1) ^ c := by
rw [Real.sq_sqrt]
swap; ยท exact mul_nonneg (by positivity) (Real.log_nonneg (by simp))
field_simp
rw [โ Real.log_rpow (by positivity), โ Real.log_inv,
Real.exp_log (by positivity), one_div, ENNReal.ofReal_inv_of_pos (by positivity),
โ ENNReal.ofReal_rpow_of_nonneg (by positivity) (by positivity)]
norm_castActions: Source ยท Open Issue
Meaning last changed in v4.34.0-rc2-1-g439785b (2026-08-23), the 3th recorded change.
Self-contained, with its dependencies inlined and proofs replaced by sorry: download the raw file ยท open it in the Lean web editor.
Dependency graph
Audit surface: 1 project declarations, 69 external constants
โ Proved: no sorry anywhere in its closure
This is the tool's own reading of one build's recorded axioms, and it is not robust against an author who wants it to pass. Checking meant to be relied on should go through Comparator, which replays the proof through the kernel from an export against an explicit list of permitted axioms.