Sorting Jordan sequences in linear time using level-linked search trees
Information and Control
Fibonacci heaps and their uses in improved network optimization algorithms
Journal of the ACM (JACM)
A minimum spanning tree algorithm with inverse-Ackermann type complexity
Journal of the ACM (JACM)
A data structure for manipulating priority queues
Communications of the ACM
A minimum spanning tree algorithm with inverse-Ackermann type complexity
Journal of the ACM (JACM)
SODA '01 Proceedings of the twelfth annual ACM-SIAM symposium on Discrete algorithms
An optimal minimum spanning tree algorithm
Journal of the ACM (JACM)
Minimizing randomness in minimum spanning tree, parallel connectivity, and set maxima algorithms
SODA '02 Proceedings of the thirteenth annual ACM-SIAM symposium on Discrete algorithms
Randomized minimum spanning tree algorithms using exponentially fewer random bits
ACM Transactions on Algorithms (TALG)
A simpler implementation and analysis of Chazelle's soft heaps
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
Streaming algorithms for selection and approximate sorting
FSTTCS'07 Proceedings of the 27th international conference on Foundations of software technology and theoretical computer science
List heuristic scheduling algorithms for distributed memory systems with improved time complexity
ICDCN'08 Proceedings of the 9th international conference on Distributed computing and networking
Index design and query processing for graph conductance search
The VLDB Journal — The International Journal on Very Large Data Bases
Sensitivity analysis of minimum spanning trees in sub-inverse-ackermann time
ISAAC'05 Proceedings of the 16th international conference on Algorithms and Computation
LATIN'06 Proceedings of the 7th Latin American conference on Theoretical Informatics
Research paper: The saga of minimum spanning trees
Computer Science Review
Proceedings of the Twenty-Fourth ACM Symposium on Operating Systems Principles
ACM SIGOPS 24th Symposium on Operating Systems Principles
A lightweight infrastructure for graph analytics
Proceedings of the Twenty-Fourth ACM Symposium on Operating Systems Principles
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A simple variant of a priority queue, called a soft heap, is introduced. The data structure supports the usual operations: insert, delete, meld, and findmin. Its novelty is to beat the logarithmic bound on the complexity of a heap in a comparison-based model. To break this information-theoretic barrier, the entropy of the data structure is reduced by artifically raising the values of certain keys. Given any mixed sequence of n operations, a soft heap with error rate &egr; (for any 0 &egr;n of its items have their keys raised. The amortized complexity of each operation is constant, except for insert, which takes 0(log 1/&egr;)time. The soft heap is optimal for any value of &egr; in a comparison-based model. The data structure is purely pointer-based. No arrays are move items across the data structure not individually, as is customary, but in groups, in a data-structuring equivalent of “car pooling.” Keys must be raised as a result, in order to preserve the heap ordering of the data structure. The soft heap can be used to compute exact or approximate medians and percentiles optimally. It is also useful for approximate sorting and for computing minimum spanning trees of general graphs.