Computing with Noisy Information 论文
1994SIAM Journal on Computing引用 314
Complexity and Algorithms in GraphsOptimization and Search ProblemsMachine Learning and Algorithms
摘要
This paper studies the depth of noisy decision trees in which each node gives the wrong answer with some constant probability. In the noisy Boolean decision tree model, tight bounds are given on the number of queries to input variables required to compute threshold functions, the parity function and symmetric functions. In the noisy comparison tree model, tight bounds are given on the number of noisy comparisons for searching, sorting, selection and merging. The paper also studies parallel selection and sorting with noisy comparisons, giving tight bounds for several problems.