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A Reliable Randomized Algorithm for the Closest-Pair Problem
TLDR
In the course of solving the duplicate-grouping problem, a new universal class of hash functions of independent interest is described, and it is shown that both of the foregoing problems can be solved by randomized algorithms that useO(n) space and finish inO( n) time with probability tending to 1 asngrows to infinity. Expand
In-Place Calculation of Minimum-Redundancy Codes
TLDR
It is shown that if p is sorted then it is possible to calculate the array l in-place, with l i overwriting p i , in O(n) time and using O(1) additional space. Expand
Comparison of algorithms for standard median filtering
TLDR
Standard median filtering that is searched repeatedly for a median from a sample set which changes only slightly between the subsequent searches is discussed and simple variants are proposed which are especially suited for small sample sets. Expand
Characterizing Multiterminal Flow Networks and Computing Flows in Networks of Small Treewidth
TLDR
This work shows that if a flow network haskinput/output terminals, its external flow pattern has two characterizations of size independent of the total number of vertices: a set of 2k+1 inequalities inkvariables representing flow values at the terminals, and a mimicking network with at most 22kvertices and the same external flow patterns as the original network. Expand
Practical In-Place Mergesort
TLDR
The implementations of the fastest in-place mergesort behaves still about 50 per cent slower than the bottom-up heapsort, however, the implementations are practical compared to mergesorts algorithms based on in- place merging. Expand
In-Place Sorting with Fewer Moves
TLDR
This is the first in-place sorting algorithm requiring o(NLogn) moves in the worst case while guaranteeing O(nlogn) comparisons, but due to the constant factors involved the algorithm is predominantly of theoretical interest. Expand
Asymptotically efficient in-place merging
Two linear-time algorithms for in-place/ merging are presented. Both algorithms perform at most m(t+1)+n/2t+o(m) comparisons, where m and n are the sizes of the input sequences, m⩽n, andExpand
Tree Compression and Optimization with Applications
TLDR
Tree compression can be seen as a trade-off problem between time and space in which the authors can choose different strategies depending on whether they prefer better compression results or more efficient operations in the compressed structure. Expand
Heaps and Heapsort on Secondary Storage
TLDR
Using the suggested data structure, an optimal external heapsort is obtained that performs O((NIp) log CM,pj(N/P)) page transfers and O(N log, N) comparisons in the worst case when sorting N records. Expand
Branch Mispredictions Don't Affect Mergesort
TLDR
By decoupling element comparisons from branches, this paper can avoid most negative effects caused by branch mispredictions in quicksort and describe an in-situ version of mergesort that provides the same bounds, but uses only O(log2n) words of extra memory. Expand
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