105 research outputs found
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Combinatorics, Probability and Computing
One of the exciting phenomena in mathematics in recent years has been the widespread and surprisingly effective use of probabilistic methods in diverse areas. The probabilistic point of view has turned out to b
Book of Abstracts of the Sixth SIAM Workshop on Combinatorial Scientific Computing
Book of Abstracts of CSC14 edited by Bora UçarInternational audienceThe Sixth SIAM Workshop on Combinatorial Scientific Computing, CSC14, was organized at the Ecole Normale Supérieure de Lyon, France on 21st to 23rd July, 2014. This two and a half day event marked the sixth in a series that started ten years ago in San Francisco, USA. The CSC14 Workshop's focus was on combinatorial mathematics and algorithms in high performance computing, broadly interpreted. The workshop featured three invited talks, 27 contributed talks and eight poster presentations. All three invited talks were focused on two interesting fields of research specifically: randomized algorithms for numerical linear algebra and network analysis. The contributed talks and the posters targeted modeling, analysis, bisection, clustering, and partitioning of graphs, applied in the context of networks, sparse matrix factorizations, iterative solvers, fast multi-pole methods, automatic differentiation, high-performance computing, and linear programming. The workshop was held at the premises of the LIP laboratory of ENS Lyon and was generously supported by the LABEX MILYON (ANR-10-LABX-0070, Université de Lyon, within the program ''Investissements d'Avenir'' ANR-11-IDEX-0007 operated by the French National Research Agency), and by SIAM
A sheaf-theoretic approach to pattern matching and related problems
AbstractWe present a general theory of pattern matching by adopting an extensional, geometric view of patterns. Representing the geometry of the pattern via a Grothendieck topology, the extension of the matching relation for a constant target and varying pattern forms a sheaf. We derive a generalized version of the Knuth-Morris-Pratt string-matching algorithm by gradually converting this extensional description into an intensional description, i.e., an algorithm. The generality of this approach is illustrated by briefly considering other applications: Earley's algorithm for parsing, Waltz filtering for scene analysis, matching modulo commutativity, and the n-queens problem
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Strongly Correlated Random Interacting Processes
The focus of the workshop was to discuss the recent developments and future research directions in the area of large scale random interacting processes, with main emphasis in models where local microscopic interactions either produce strong correlations at macroscopic levels, or generate non-equilibrium dynamics. This report contains extended abstracts of the presentations, which featured research in several directions including selfinteracting random walks, spatially growing processes, strongly dependent percolation, spin systems with long-range order, and random permutations
Self-Evaluation Applied Mathematics 2003-2008 University of Twente
This report contains the self-study for the research assessment of the Department of Applied Mathematics (AM) of the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) at the University of Twente (UT). The report provides the information for the Research Assessment Committee for Applied Mathematics, dealing with mathematical sciences at the three universities of technology in the Netherlands. It describes the state of affairs pertaining to the period 1 January 2003 to 31 December 2008
Effective algorithms and protocols for wireless networking: a topological approach
Much research has been done on wireless sensor networks. However, most protocols
and algorithms for such networks are based on the ideal model Unit Disk Graph
(UDG) model or do not assume any model. Furthermore, many results assume the
knowledge of location information of the network. In practice, sensor networks often
deviate from the UDG model significantly. It is not uncommon to observe stable long
links that are more than five times longer than unstable short links in real wireless
networks. A more general network model, the quasi unit-disk graph (quasi-UDG)
model, captures much better the characteristics of wireless networks. However, the
understanding of the properties of general quasi-UDGs has been very limited, which
is impeding the design of key network protocols and algorithms.
In this dissertation we study the properties for general wireless sensor networks
and develop new topological/geometrical techniques for wireless sensor networking.
We assume neither the ideal UDG model nor the location information of the nodes.
Instead we work on the more general quasi-UDG model and focus on figuring out
the relationship between the geometrical properties and the topological properties of
wireless sensor networks. Based on such relationships we develop algorithms that can
compute useful substructures (planar subnetworks, boundaries, etc.). We also present direct applications of the properties and substructures we constructed including routing,
data storage, topology discovery, etc.
We prove that wireless networks based on quasi-UDG model exhibit nice properties
like separabilities, existences of constant stretch backbones, etc. We develop
efficient algorithms that can obtain relatively dense planar subnetworks for wireless
sensor networks. We also present efficient routing protocols and balanced data storage
scheme that supports ranged queries.
We present algorithmic results that can also be applied to other fields (e.g., information
management). Based on divide and conquer and improved color coding
technique, we develop algorithms for path, matching and packing problem that significantly
improve previous best algorithms. We prove that it is unlikely for certain
problems in operation science and information management to have any relatively
effective algorithm or approximation algorithm for them
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