Relaxed heaps: an alternative to Fibonacci heaps with applications to parallel computation
Communications of the ACM
A balanced search tree with O(1) worst case update time
Acta Informatica
An implicit binomial queue with constant insertion time
No. 318 on SWAT 88: 1st Scandinavian workshop on algorithm theory
Average-case lower bounds for searching
SIAM Journal on Computing
A Simple Balanced Search Tree with O(1) Worst-Case Update Time
ISAAC '93 Proceedings of the 4th International Symposium on Algorithms and Computation
WADS '95 Proceedings of the 4th International Workshop on Algorithms and Data Structures
Proceedings of the tenth annual ACM-SIAM symposium on Discrete algorithms
Lower bounds for external memory dictionaries
SODA '03 Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete algorithms
The Complexity of Constructing Evolutionary Trees Using Experiments
ICALP '01 Proceedings of the 28th International Colloquium on Automata, Languages and Programming,
On Assigning Prefix Free Codes to the Vertices of a Graph
COCOON '01 Proceedings of the 7th Annual International Conference on Computing and Combinatorics
An optimal dynamic interval stabbing-max data structure?
SODA '05 Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms
Dynamic planar range maxima queries
ICALP'11 Proceedings of the 38th international colloquim conference on Automata, languages and programming - Volume Part I
Path minima queries in dynamic weighted trees
WADS'11 Proceedings of the 12th international conference on Algorithms and data structures
Computer Science Review
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The complexity of maintaining a set under the operations Insert, Delete and FindMin is considered. In the comparison model it is shown that any randomized algorithm with expected amortized cost t comparisons per Insert and Delete has expected cost at least n/(e22t)-1 comparisons for FindMin. If FindMin is replaced by a weaker operation. FindAny, then it is shown that a randomized algorithm with constant expected cost per operation exists; in contrast, it is shown that no deterministic algorithm can have constant cost per operation. Finally, a deterministic algorithm with constant amortized cost per operation for an offline version of the problem is given.