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Odile Marcotte

dblp:20/2911 · also Odile M.-C. Marcotte · DBLP profile ↗
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7ranked-venue papers
3as first author
0since 2021 · last 2006
0000-0002-8015-2084ORCID · corroborated

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

Theory of computation · 5 · 3 first-authorComputer networks · 1Graphics, computer vision, multimedia, augmented reality and games · 1

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
3 papers
Computational geometry · 44% Algorithmic game theory and mechanism design · 22% Graph algorithms and graph theory · 15%

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

TopicWeightPapersLastEvidence papers
Computational geometry
geometric matching
0.031991
Fast Matching Algorithms for Points on a Polygon · SIAM J. Comput. 1991
Fast Matching Algorithms for Points on a Polygon (Extended Abstract) · FOCS 1989
On Geometric Matching · SCG 1989
Algorithmic game theory and mechanism design › matching › perfect matching
minimum-weight perfect matching
0.021991
Fast Matching Algorithms for Points on a Polygon · SIAM J. Comput. 1991
Fast Matching Algorithms for Points on a Polygon (Extended Abstract) · FOCS 1989
Computational geometry › visibility
polygon visibility
0.021991
Fast Matching Algorithms for Points on a Polygon (Extended Abstract) · FOCS 1989
Fast Matching Algorithms for Points on a Polygon · SIAM J. Comput. 1991
Graph algorithms and graph theory › graph matching
matching algorithms
0.011991
Fast Matching Algorithms for Points on a Polygon · SIAM J. Comput. 1991
Mathematical optimization › combinatorial optimization
assignment problem
0.011989
Fast Matching Algorithms for Points on a Polygon (Extended Abstract) · FOCS 1989
Algorithms and data structures › combinatorial algorithms
minimum-weight matching
0.011989
On Geometric Matching · SCG 1989
Graph algorithms and graph theory › graph matching
maximum matching
0.011989
On Geometric Matching · SCG 1989

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

geometric data structures · 0.0divide-and-conquer · 0.0graph algorithms · 0.0euclidean distance · 0.0dynamic programming · 0.0
YearPublicationVenuePosition
2006 Adaptation Scenarios for New Media Artworks
abstract
Artists in new media arts explore the possibilities offered by digital technologies to create adaptive and interactive new media artworks integrating audio and video. In this paper, we are interested in adaptation mechanisms for such artworks and we focus on the design and implementation of adaptation scenarios. We formalize adaptation scenarios by using the event-condition-action paradigm and we introduce the concept of adaptation policy. We present the adaptation engine we have designed and prototyped to manage and execute adaptation scenarios
Anis Ouali, Brigitte Kerhervé, Odile Marcotte, Paul Landon
ICME3
2002 Erratum to "Comparison of column generation models for channel assignment in cellular networks"
Brigitte Jaumard, Odile Marcotte, Christophe Meyer, Tsevi Vovor
Discret. Appl. Math.2
2001 Comparison of column generation models for channel assignment in cellular networks
Brigitte Jaumard, Odile Marcotte, Christophe Meyer, Tsevi Vovor
Discret. Appl. Math.2
1997 Heuristics for Ring Network Design When Several Types of Switches are Available
abstract
We consider a model for communications network design that includes the optimal location of switches (of which there are several types) and the design of the access and backbone networks. The model is of the integer programming variety, and in order to find its solution, we propose a greedy heuristic that yields a good starting solution and a more sophisticated heuristic based on tabu search. Finally we present numerical results for problems including as much as 200 user sites and 20 potential switch sites.
Steven Chamberland, Brunilde Sansò, Odile Marcotte
ICC (2)3
1991 Fast Matching Algorithms for Points on a Polygon
abstract
Given a set P of $2n$ points on the boundary of a polygon, consider the complete graph whose vertex set is P, and whose edges are assigned weights equal to the Euclidean distance between their endpoints if the endpoints see each other in the polygon and $ + \infty $ otherwise. The problem of finding a minimum-weightperfect matching is investigated in this graph, and an $O(n\log (n))$ time algorithm is obtained if the polygon is convex; an $O(n\log ^2 (n))$ time algorithm is obtained if the polygon is simple but not convex. Similar results are obtained for the assignment problem and the maximum-weight problem.
Odile Marcotte, Subhash Suri
SIAM J. Comput.1
1989 On Geometric Matching
abstract
An Ο(n3/2√α(n)) time algorithm is presented for finding a minimum-weight matching of a set of 2n points lying on the boundary of a convex polygon, where α(n) is the functional inverse of the Ackerman's function. Generalizing this result, we obtain an Ο(n3/2 logn√α(n)) time algorithm for the minimum-weight matching of points lying on the boundary of a simple nonconvex polygon, where we require that the line segments joining the matched pairs be contained within the polygon. We also consider the maximum-weight matching problem, and obtain algorithms of complexities Ο(n) and Ο(n log n) for the convex and the nonconvex case, respectively. By contrast, finding a weighted matching of an arbitrary set of points takes Ο(n5/2 log4 n) time [Vaidya 1987].
Odile Marcotte, Subhash Suri
SCG1
1989 Fast Matching Algorithms for Points on a Polygon (Extended Abstract)
abstract
The complete graph induced by a set of 2n points on the boundary of a polygon is considered. The edges are assigned weights equal to the Euclidean distance between their endpoints if the endpoints see each other in the polygon, and + infinity otherwise. An O(n log n)-time algorithm is obtained for finding a minimum-weight perfect matching in this graph if the polygon is convex, and an O(n log/sup 2/n)-time algorithm if the polygon is simple but nonconvex. The assignment problem for a convex polygon is solved in time O(n log n), and O(n alpha (n)) and O(n alpha (n) log n) time bounds are obtained for the verification problem on convex and nonconvex polygons, respectively, where alpha (n) is the functional inverse of the Ackermann function.>
Odile Marcotte, Subhash Suri
FOCS1