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Ramana M. Idury

dblp:44/3655 · DBLP profile ↗
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10ranked-venue papers
7as first author
0since 2021 · last 1996
—ORCID · none

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

Theory of computation · 8 · 5 first-authorGraphics, computer vision, multimedia, augmented reality and games · 2 · 2 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
4 papers
Algorithms and data structures · 100%

Topics — the 7 heaviest of 8, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Algorithms and data structures › sequence algorithms › string algorithms › string matching
dictionary matching
0.021995
Improved Dynamic Dictionary Matching · Inf. Comput. 1995
Improved Dynamic Dictionary Matching · SODA 1993
Algorithms and data structures › sequence algorithms › string algorithms › string matching
multiple pattern matching
0.021995
Multiple Matching of Rectangular Patterns · Inf. Comput. 1995
Multiple matching of rectangular patterns · STOC 1993
Algorithms and data structures › sequence algorithms
string algorithms
0.021995
Improved Dynamic Dictionary Matching · Inf. Comput. 1995
Improved Dynamic Dictionary Matching · SODA 1993
Algorithms and data structures › sequence algorithms › string algorithms
string matching
0.021995
Multiple Matching of Rectangular Patterns · Inf. Comput. 1995
Multiple matching of rectangular patterns · STOC 1993
Algorithms and data structures
dynamic algorithms
0.021995
Improved Dynamic Dictionary Matching · Inf. Comput. 1995
Improved Dynamic Dictionary Matching · SODA 1993
Algorithms and data structures › sequence algorithms › string algorithms
dynamic dictionary matching
0.011995
Improved Dynamic Dictionary Matching · Inf. Comput. 1995
Algorithms and data structures › sequence algorithms › string algorithms
combinatorial pattern matching
0.011995
Improved Dynamic Dictionary Matching · Inf. Comput. 1995

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

string matching · 0.0multidimensional range searching · 0.0
YearPublicationVenuePosition
1996 Multiple Matching of Parametrized Patterns
Ramana M. Idury, Alejandro A. Schäffer
Theor. Comput. Sci.1
1995 Improved Dynamic Dictionary Matching
Amihood Amir, Martin Farach-Colton, Ramana M. Idury, Han La Poutré, Alejandro A. Schäffer
Inf. Comput.3
1995 Multiple Matching of Rectangular Patterns
Ramana M. Idury, Alejandro A. Schäffer
Inf. Comput.1
1994 Multiple Matching of Parameterized Patterns
Ramana M. Idury, Alejandro A. Schäffer
CPM1
1994 Faster Isometric Embedding in Products of Complete Graphs
Franz Aurenhammer, Michael Formann, Ramana M. Idury, Alejandro A. Schäffer, Frank Geraets
Discret. Appl. Math.3
1994 Dynamic Dictionary Matching with Failure Functions
Ramana M. Idury, Alejandro A. Schäffer
Theor. Comput. Sci.1
1993 Improved Dynamic Dictionary Matching
Amihood Amir, Martin Farach-Colton, Ramana M. Idury, Han La Poutré, Alejandro A. Schäffer
SODA3
1993 Multiple matching of rectangular patterns
abstract
We describe the first .efiicientalgorithm for simultaneously matching multiple rectangular patterns of varying sizes and aspect, ratios in a rectangular text.Efficient means significantly better asymptotically than known al,qorithrns that handle one height, width, or aspect ratio at a time.Our algorithm features an interesting use of multidimensional range searching, as well as new adaptations of several known techniques for two climensional string matching.We also extend our algorithm to a dynamic setting where the set of patterns can change over time. 1 Machinery.
Ramana M. Idury, Alejandro A. Schäffer
STOC1
1993 Triangulating Three-Colored Graphs in Linear Time and Linear Space
abstract
Kannan and Warnow [Triangulating Three-Colored Graphs, Proc. 2nd SODA, 1991, pp. 337–343 and SIAM J. Discrete Math., 5 (1992), pp. 249–258] describe an algorithm to decide whether a three-colored graph can be triangulated so that all the edges connect vertices of different colors. This problem is motivated by a problem in evolutionary biology. Kannan and Warnow have two implementation strategies for their algorithm: one uses slightly superlinear time, while the other uses linear time but quadratic space. We note that three-colored triangulatable graphs are always planar, and we use this fact to modify Kannan and Warnow’s algorithm to obtain an algorithm that uses both linear time and linear space.
Ramana M. Idury, Alejandro A. Schäffer
SIAM J. Discret. Math.1
1992 Dynamic Dictionary Matching with Failure Functions (Extended Abstract)
Ramana M. Idury, Alejandro A. Schäffer
CPM1