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116
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STACS
2001
Springer
15 years 7 months ago
Approximation Algorithms for the Bottleneck Stretch Factor Problem
The stretch factor of a Euclidean graph is the maximum ratio of the distance in the graph between any two points and their Euclidean distance. Given a set S of n points in Rd, we ...
Giri Narasimhan, Michiel H. M. Smid
131
Voted
FSTTCS
2006
Springer
15 years 6 months ago
Approximation Algorithms for 2-Stage Stochastic Optimization Problems
Abstract. Stochastic optimization is a leading approach to model optimization problems in which there is uncertainty in the input data, whether from measurement noise or an inabili...
Chaitanya Swamy, David B. Shmoys
103
Voted
SIAMCOMP
2008
123views more  SIAMCOMP 2008»
15 years 2 months ago
Approximation Algorithms for Biclustering Problems
One of the main goals in the analysis of microarray data is to identify groups of genes and groups of experimental conditions (including environments, individuals, and tissues) tha...
Lusheng Wang, Yu Lin, Xiaowen Liu
127
Voted
ICAC
2006
IEEE
15 years 8 months ago
Hardness of Approximation and Greedy Algorithms for the Adaptation Problem in Virtual Environments
— Over the past decade, wide-area distributed computing has emerged as a powerful computing paradigm. Virtual machines greatly simplify wide-area distributed computing ing the ab...
Ananth I. Sundararaj, Manan Sanghi, John R. Lange,...
SIGMOD
2001
ACM
200views Database» more  SIGMOD 2001»
16 years 2 months ago
Data Bubbles: Quality Preserving Performance Boosting for Hierarchical Clustering
In this paper, we investigate how to scale hierarchical clustering methods (such as OPTICS) to extremely large databases by utilizing data compression methods (such as BIRCH or ra...
Markus M. Breunig, Hans-Peter Kriegel, Peer Kr&oum...