How to learn an unknown environment. I: the rectilinear case
Journal of the ACM (JACM)
Fast Estimation of Diameter and Shortest Paths (Without Matrix Multiplication)
SIAM Journal on Computing
Fast Approximation Algorithms for the Knapsack and Sum of Subset Problems
Journal of the ACM (JACM)
Computing the median with uncertainty
STOC '00 Proceedings of the thirty-second annual ACM symposium on Theory of computing
On computing functions with uncertainty
PODS '01 Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Offering a Precision-Performance Tradeoff for Aggregation Queries over Replicated Data
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
ICALP '89 Proceedings of the 16th International Colloquium on Automata, Languages and Programming
On Some Tighter Inapproximability Results
On Some Tighter Inapproximability Results
An algorithm for the relative robust shortest path problem with interval data
An algorithm for the relative robust shortest path problem with interval data
Efficient update strategies for geometric computing with uncertainty
CIAC'03 Proceedings of the 5th Italian conference on Algorithms and complexity
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We consider the problem of estimating the length of a shortest path in a DAG whose edge lengths are known only approximately but can be determined exactly at a cost. Initially, each edge e is known only to lie within an interval [le, he]; the estimation algorithm can pay ce to find the exact length of e. In particular, we study the problem of finding the cheapest set of edges such that, if exactly these edges are queried, the length of the shortest path will be known, within an additive 驴 0 that is given as an input parameter. We study both the general problem and several special cases, and obtain both easiness and hardness approximation results.