claimroutineinferred_dep
Layer-cake bound on capped min-expectation
Statement (paper)
With , , , and , we have
In plain English
The expectation of on the event under the edge measure is written as an integral over of the edge mass of . Expansion and Cauchy–Schwarz bound it by , which is at most , where .
Why it's here
The layer-cake formula turns the min into an integral of joint edge masses of the superlevel sets and . The expansion bound from the incidence piece gives . Using the cap and the marginal lower bound with , this is at most , and Cauchy–Schwarz in finishes. The resulting factor in front of is what the next step, absorbing the tail moment by Young's inequality, needs.
Classified routine:
A layer-cake formula followed by Cauchy–Schwarz in the level parameter, applied to the expansion bound supplied by the inc-piece proposition. It is standard bookkeeping inside the tail estimate.
Uses
Used by
Sources
PaperOpen
- Section
- §7.1 A pointwise estimate and its tail consequence
- Page
- —
- Label
—- Line
sections/06-extraction.tex:142
Leannot aligned
Phase 2 aligns this node to a Lean declaration.
Friction
- infoinferred_depoutline: "Layer-cake expansion bound on capped expectation" rests on inc:piece