A coding theorem for distributed computation
STOC '94 Proceedings of the twenty-sixth annual ACM symposium on Theory of computing
Lower bounds for noisy Boolean decision trees
STOC '96 Proceedings of the twenty-eighth annual ACM symposium on Theory of computing
A theorem on sensitivity and applications in private computation
STOC '99 Proceedings of the thirty-first annual ACM symposium on Theory of computing
Error-resilient DNA computation
Proceedings of the seventh annual ACM-SIAM symposium on Discrete algorithms
Computation in noisy radio networks
Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
Searching games with errors---fifty years of coping with liars
Theoretical Computer Science
Computing Boolean Functions from Multiple Faulty Copies of Input Bits
LATIN '02 Proceedings of the 5th Latin American Symposium on Theoretical Informatics
Computing Boolean functions from multiple faulty copies of input bits
Theoretical Computer Science - Latin American theorotical informatics
Energy Bounds for Fault-Tolerant Nanoscale Designs
Proceedings of the conference on Design, Automation and Test in Europe - Volume 1
Rounds vs queries trade-off in noisy computation
SODA '05 Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms
Lower Bounds for the Noisy Broadcast Problem
FOCS '05 Proceedings of the 46th Annual IEEE Symposium on Foundations of Computer Science
Reliable computations based on locally decodable codes
STACS'06 Proceedings of the 23rd Annual conference on Theoretical Aspects of Computer Science
Making polynomials robust to noise
STOC '12 Proceedings of the forty-fourth annual ACM symposium on Theory of computing
Energy-efficient circuit design
Proceedings of the 5th conference on Innovations in theoretical computer science
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Boolean circuits in which gates independently make errors with probability (at most) epsilon are considered. It is shown that the critical number crit(f) of a function f yields lower bound Omega (crit(f) log crit (f)) for the noisy circuit size. The lower bound is proved for an even stronger computational model, static Boolean decision trees with erroneous answers. A decision tree is static if the questions it asks do not depend on previous answers. The depth of such a tree provides a lower bound on the number of gates that depend directly on some input and hence on the size of a noisy circuit. Furthermore, it is shown that an Omega (n log n) lower bound holds for almost all Boolean n-input functions with respect to the depth of noisy dynamic decision trees. This bound is the best possible and implies that almost all n-input Boolean functions have noisy decision tree complexity Theta (n log n) in the static as well as in the dynamic case.