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Dmitry Keselman

dblp:16/5466 · DBLP profile ↗
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3ranked-venue papers
1as first author
0since 2021 · last 1999
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Theory of computation · 3 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
2 papers
Algorithms and data structures · 46% Graph algorithms and graph theory · 23% Approximation and online algorithms · 23%

Topics — the 4 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Approximation and online algorithms
approximation algorithms		 0.021997
Maximum Agreement Subtree in a Set of Evolutionary Trees: Metrics and Efficient Algorithms · SIAM J. Comput. 1997
Maximum Agreement Subtree in a Set of Evolutionary Trees-Metrics and Efficient Algorithms · FOCS 1994
Algorithms and data structures
computational biology		 0.021997
Maximum Agreement Subtree in a Set of Evolutionary Trees: Metrics and Efficient Algorithms · SIAM J. Comput. 1997
Maximum Agreement Subtree in a Set of Evolutionary Trees-Metrics and Efficient Algorithms · FOCS 1994
Graph algorithms and graph theory › graph algorithms › tree algorithms
maximum agreement subtree		 0.021997
Maximum Agreement Subtree in a Set of Evolutionary Trees: Metrics and Efficient Algorithms · SIAM J. Comput. 1997
Maximum Agreement Subtree in a Set of Evolutionary Trees-Metrics and Efficient Algorithms · FOCS 1994
Algorithms and data structures › computational biology
phylogenetic trees		 0.021997
Maximum Agreement Subtree in a Set of Evolutionary Trees: Metrics and Efficient Algorithms · SIAM J. Comput. 1997
Maximum Agreement Subtree in a Set of Evolutionary Trees-Metrics and Efficient Algorithms · FOCS 1994

Methods — techniques the papers use, named apart from their topics

bounded-degree tree algorithms · 0.0dynamic programming · 0.0
YearPublicationVenuePosition
1999 Indexing and Dictionary Matching with One Error
Amihood Amir, Dmitry Keselman, Gad M. Landau, Moshe Lewenstein, Noa Lewenstein, Michael Rodeh
 WADS2
1997 Maximum Agreement Subtree in a Set of Evolutionary Trees: Metrics and Efficient Algorithms
abstract
The maximum agreement subtree approach is one method of reconciling different evolutionary trees for the same set of species. An agreement subtree enables choosing a subset of the species for whom the restricted subtree is equivalent (under a suitable definition) in all given evolutionary trees. Recently, dynamic programming ideas were used to provide polynomial time algorithms for finding a maximum homeomorphic agreement subtree of two trees. Generalizing these methods to sets of more than two trees yields algorithms that are exponential in the number of trees. Unfortunately, it turns out that in reality one is usually presented with more than two trees, sometimes as many as thousands of trees. In this paper we prove that the maximum homeomorphic agreement subtree problem is $\cal{NP}$-complete for three trees with unbounded degrees. We then show an approximation algorithm of time O(kn5) for choosing the species that are not in a maximum agreement subtree of a set of k trees. Our approximation is guaranteed to provide a set that is no more than 4 times the optimum solution. While the set of evolutionary trees may be large in practice, the trees usually have very small degrees, typically no larger than three. We develop a new method for finding a maximum agreement subtree of k trees, of which one has degree bounded by d. This new method enables us to find a maximum agreement subtree in time O(knd + 1+ n2d).
Amihood Amir, Dmitry Keselman
 SIAM J. Comput.2
1994 Maximum Agreement Subtree in a Set of Evolutionary Trees-Metrics and Efficient Algorithms
abstract
In this paper we prove that the maximum homeomorphic agreement subtree problem is /spl Nscr//spl Pscr/-complete for three trees with unbounded degrees. We then show an approximation algorithm of time O(kn/sup 5/) for choosing the species that are not in a maximum agreement subtree of a set of k trees. Our approximation is guaranteed to provide a set that is no more than 4 times the optimum solution. While the set of evolutionary trees may be large in practice, the trees usually have very small degrees, typically no larger than three. We develop a new method for finding a maximum agreement subtree of k trees, of which one has degree bounded by d. This new method enables us to find a maximum agreement subtree in time O(kn/sup d+1/).>
Dmitry Keselman, Amihood Amir
 FOCS1