concentration bounds
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Author(s):  
JACOB FOX ◽  
MATTHEW KWAN ◽  
LISA SAUERMANN

Abstract We prove several different anti-concentration inequalities for functions of independent Bernoulli-distributed random variables. First, motivated by a conjecture of Alon, Hefetz, Krivelevich and Tyomkyn, we prove some “Poisson-type” anti-concentration theorems that give bounds of the form 1/e + o(1) for the point probabilities of certain polynomials. Second, we prove an anti-concentration inequality for polynomials with nonnegative coefficients which extends the classical Erdős–Littlewood–Offord theorem and improves a theorem of Meka, Nguyen and Vu for polynomials of this type. As an application, we prove some new anti-concentration bounds for subgraph counts in random graphs.


Stat ◽  
2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Debolina Paul ◽  
Saptarshi Chakraborty ◽  
Swagatam Das

2021 ◽  
pp. 177-208
Author(s):  
Siyao Guo ◽  
Qian Li ◽  
Qipeng Liu ◽  
Jiapeng Zhang
Keyword(s):  

2021 ◽  
Author(s):  
Drew Fudenberg ◽  
Giacomo Lanzani ◽  
Philipp Strack
Keyword(s):  

Author(s):  
Anders Aamand ◽  
Jakob Bæk Tejs Knudsen ◽  
Mathias Bæk Tejs Knudsen ◽  
Peter Michael Reichstein Rasmussen ◽  
Mikkel Thorup

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