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» Randomized Algorithms and Complexity Theory
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143
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MCS
2007
Springer
15 years 9 months ago
Selecting Diversifying Heuristics for Cluster Ensembles
Abstract. Cluster ensembles are deemed to be better than single clustering algorithms for discovering complex or noisy structures in data. Various heuristics for constructing such ...
Stefan Todorov Hadjitodorov, Ludmila I. Kuncheva
148
Voted
SAC
2008
ACM
15 years 3 months ago
A biologically inspired generation of virtual characters
A number of techniques for generating geometric models of human head and body are in use nowadays. Models of human characters are useful in computer games, virtual reality, and ma...
Roberto C. Cavalcante Vieira, Creto Augusto Vidal,...
185
Voted
COMPGEOM
2010
ACM
15 years 8 months ago
A dynamic data structure for approximate range searching
In this paper, we introduce a simple, randomized dynamic data structure for storing multidimensional point sets, called a quadtreap. This data structure is a randomized, balanced ...
David M. Mount, Eunhui Park
152
Voted
ICIP
2009
IEEE
15 years 1 months ago
Randomness-in-Structured Ensembles for compressed sensing of images
Leading compressed sensing (CS) methods require m = O (k log(n)) compressive samples to perfectly reconstruct a k-sparse signal x of size n using random projection matrices (e.g., ...
Abdolreza A. Moghadam, Hayder Radha
232
Voted
GIS
2006
ACM
16 years 4 months ago
Computing longest duration flocks in trajectory data
Moving point object data can be analyzed through the discovery of patterns. We consider the computational efficiency of computing two of the most basic spatio-temporal patterns in...
Joachim Gudmundsson, Marc J. van Kreveld