Improved upper bounds for time-space trade-offs for selection
Nordic Journal of Computing
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Nordic Journal of Computing
An in-place sorting with O(nlog n) comparisons and O(n) moves
Journal of the ACM (JACM)
Comparison-based time-space lower bounds for selection
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
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Emerging Trends in Visual Computing
Comparison-based time-space lower bounds for selection
ACM Transactions on Algorithms (TALG)
SOFSEM'11 Proceedings of the 37th international conference on Current trends in theory and practice of computer science
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STACS'05 Proceedings of the 22nd annual conference on Theoretical Aspects of Computer Science
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ISAAC'06 Proceedings of the 17th international conference on Algorithms and Computation
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WALCOM'10 Proceedings of the 4th international conference on Algorithms and Computation
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ISAAC'11 Proceedings of the 22nd international conference on Algorithms and Computation
Time-Space tradeoffs for all-nearest-larger-neighbors problems
WADS'13 Proceedings of the 13th international conference on Algorithms and Data Structures
Reprint of: Memory-constrained algorithms for simple polygons
Computational Geometry: Theory and Applications
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Selecting an element of given rank, for example the median, is afundamental problem in data organization and the computationalcomplexity of comparison based problems. Here, we consider the scenarioin which the data resides in an array of read-only memory and hence theelements cannot be moved within the array. Under this model, we developefficient selection algorithms using very little extra space(ologn extra storage cells). These include anOn1+3 worst case algorithm and an Onloglogn average case algorithm, both using a constant numberof extra storage cells or indices. Our algorithms complement the upperbounds for the time-space tradeoffs obtained by Munro and Paterson [9]and Frederickson [4] who developed algorithms for selection in the samemodel when Wlogn2 extra storage cells are available.We apply our selection algorithms to obtain sorting algorithms thatperform the minimum number of data moves on any given array. We alsoderive upper bounds for time-space tradeoffs for sorting with minimumdata movement.—Authors' Abstract