Amortized efficiency of list update and paging rules
Communications of the ACM
Amortized analyses of self-organizing sequential search heuristics
Communications of the ACM - Lecture notes in computer science Vol. 174
Self-adjusting binary search trees
Journal of the ACM (JACM)
Communications of the ACM
Off-line algorithms for the list update problem
Information Processing Letters
Online computation and competitive analysis
Online computation and competitive analysis
On self-organizing sequential search heuristics
Communications of the ACM
Upper bounds for maximally greedy binary search trees
WADS'11 Proceedings of the 12th international conference on Algorithms and data structures
Paging for multi-core shared caches
Proceedings of the 3rd Innovations in Theoretical Computer Science Conference
Optimal strategies for the list update problem under the MRM alternative cost model
Information Processing Letters
An O(log log n)-competitive binary search tree with optimal worst-case access times
SWAT'10 Proceedings of the 12th Scandinavian conference on Algorithm Theory
A new perspective on list update: probabilistic locality and working set
WAOA'11 Proceedings of the 9th international conference on Approximation and Online Algorithms
Paging and list update under bijective analysis
Journal of the ACM (JACM)
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We re-examine offline techniques for linear search. Under a reasonable model of computation, a method is given to perform offline linear search in amortized cost proportional to the entropy of the request sequence; and so, this cost is at most logarithmic. On the other hand, any online technique is subject to linear amortized cost for some sequences. It follows, then, that no online technique can have an amortized cost of that which one could obtain if given the request sequence in advance, i.e., there is no competitive linear search algorithm.