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SODA
2000
ACM
127views Algorithms» more  SODA 2000»
13 years 10 months ago
Dimensionality reduction techniques for proximity problems
In this paper we give approximation algorithms for several proximity problems in high dimensional spaces. In particular, we give the rst Las Vegas data structure for (1 + )-neares...
Piotr Indyk
PAMI
2006
141views more  PAMI 2006»
13 years 8 months ago
Diffusion Maps and Coarse-Graining: A Unified Framework for Dimensionality Reduction, Graph Partitioning, and Data Set Parameter
We provide evidence that non-linear dimensionality reduction, clustering and data set parameterization can be solved within one and the same framework. The main idea is to define ...
Stéphane Lafon, Ann B. Lee
TMC
2010
109views more  TMC 2010»
13 years 7 months ago
Uncertainty Modeling and Reduction in MANETs
—Evaluating and quantifying trust stimulates collaboration in mobile ad hoc networks (MANETs). Many existing reputation systems sharply divide the trust value into right or wrong...
Feng Li, Jie Wu
ENTCS
2010
118views more  ENTCS 2010»
13 years 6 months ago
Fragments-based Model Reduction: Some Case Studies
Molecular biological models usually suffer from a dramatic combinatorial blow up. Indeed, proteins form complexes and can modify each others, which leads to the formation of a hug...
Jérôme Feret
SODA
2012
ACM
223views Algorithms» more  SODA 2012»
11 years 11 months ago
Data reduction for weighted and outlier-resistant clustering
Statistical data frequently includes outliers; these can distort the results of estimation procedures and optimization problems. For this reason, loss functions which deemphasize ...
Dan Feldman, Leonard J. Schulman