AND testing and robust judgement aggregation
AND testing and robust judgement aggregation
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AND 测试和稳健的判断聚合
DOI:
10.1145/3357713.3384254
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发表时间:
2020
期刊:
影响因子:
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通讯作者:
Mossel, E.
中科院分区:
文献类型:
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作者:
Filmus, Y;Lifshitz, N;Minzer, D;Mossel, E.
A functionf∶{0,1}n→ {0,1} is called an approximate AND-homomorphism if choosingx,y∈nuniformly at random, we have thatf(x∧y) =f(x)∧f(y) with probability at least 1−ε, wherex∧y= (x1∧y1,…,xn∧yn). We prove that iff∶ {0,1}n→ {0,1} is an approximate AND-homomorphism, thenfis δ-close to either a constant function or an AND function, where δ(ε) → 0 as ε→ 0. This improves on a result of Nehama, who proved a similar statement in which δ depends onn.Our theorem implies a strong result on judgement aggregation in computational social choice. In the language of social choice, our result shows that iffis ε-close to satisfying judgement aggregation, then it is δ(ε)-close to an oligarchy (the name for the AND function in social choice theory). This improves on Nehama’s result, in which δ decays polynomially withn.Our result follows from a more general one, in which we characterize approximate solutions to the eigenvalue equationf= λg, where is the downwards noise operatorf(x) =y[f(x∧y)],fis [0,1]-valued, andgis {0,1}-valued. We identify all exact solutions to this equation, and show that any approximate solution in whichfand λgare close is close to an exact solution.