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We consider Boolean functions f:{-1,1}^n->{-1,1} that are close to a sum of independent functions on mutually exclusive subsets of the variables. We prove that any such function is close to just a single function on a single subset. We also consider Boolean functions f:R^n->{-1,1} that are close, with respect to any product distribution over R^n, to a sum of their variables. We prove that any such function is close to one of the variables. Both our results are independent of the number of variables, but depend on the variance of f. I.e., if f is epsilon*Var(f)-close to a sum of independent functions or random variables, then it is O(epsilon)-close to one of the independent functions or random variables, respectively. We prove that this dependence on Var(f) is tight. Our results are a generalization of the Friedgut-Kalai-Naor Theorem [FKN02], which holds for functions f:{-1,1}^n->{-1,1} that are close to a linear combination of uniformly distributed Boolean variables.
We initiate the study of Boolean function analysis on high-dimensional expanders. We give a random-walk based definition of high dimensional expansion, which coincides with the earlier definition in terms of two-sided link expanders. Using this defin
We study the volatility of the output of a Boolean function when the input bits undergo a natural dynamics. For $n = 1,2,ldots$, let $f_n:{0,1}^{m_n} ra {0,1}$ be a Boolean function and $X^{(n)}(t)=(X_1(t),ldots,X_{m_n}(t))_{t in [0,infty)}$ be a vec
We study parity decision trees for Boolean functions. The motivation of our study is the log-rank conjecture for XOR functions and its connection to Fourier analysis and parity decision tree complexity. Let f be a Boolean function with Fourier suppor
We examine a new path transform on 1-dimensional simple random walks and Brownian motion, the quantile transform. This transformation relates to identities in fluctuation theory due to Wendel, Port, Dassios and others, and to discrete and Browni
Let $mathcal{H}$ denote a collection of subsets of ${1,2,ldots,n}$, and assign independent random variables uniformly distributed over $[0,1]$ to the $n$ elements. Declare an element $p$-present if its corresponding value is at most $p$. In this pape