Optimal Information Gathering on the Internet with Time and Cost Constraints
SIAM Journal on Computing
Query strategies for priced information
Journal of Computer and System Sciences - Special issue on STOC 2000
Efficient information gathering on the Internet
FOCS '96 Proceedings of the 37th Annual Symposium on Foundations of Computer Science
Adaptive ordering of pipelined stream filters
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Proceedings of the thirty-seventh annual ACM symposium on Theory of computing
A new strategy for querying priced information
Proceedings of the thirty-seventh annual ACM symposium on Theory of computing
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Given a function f over n binary variables, and an ordering of the n variables, we consider the Expected Decision Depth problem. Namely, what is the expected number of bits that need to be observed until the value of the function is determined, when bits of the input are observed according to the given order. Our main finding is that this problem is (essentially) #P-complete. Moreover, the hardness holds even when the function f is represented as a decision tree.