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» Approximation Algorithms for Clustering Problems
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JBI
2004
171views Bioinformatics» more  JBI 2004»
15 years 8 months ago
Consensus Clustering and Functional Interpretation of Gene Expression Data
Microarray analysis using clustering algorithms can suffer from lack of inter-method consistency in assigning related gene-expression profiles to clusters. Obtaining a consensus s...
Paul Kellam, Stephen Swift, Allan Tucker, Veronica...
CC
2007
Springer
157views System Software» more  CC 2007»
16 years 25 days ago
New Algorithms for SIMD Alignment
Optimizing programs for modern multiprocessor or vector platforms is a major important challenge for compilers today. In this work, we focus on one challenging aspect: the SIMD ALI...
Liza Fireman, Erez Petrank, Ayal Zaks
CORR
2012
Springer
235views Education» more  CORR 2012»
14 years 2 months ago
An Incremental Sampling-based Algorithm for Stochastic Optimal Control
Abstract— In this paper, we consider a class of continuoustime, continuous-space stochastic optimal control problems. Building upon recent advances in Markov chain approximation ...
Vu Anh Huynh, Sertac Karaman, Emilio Frazzoli
ICML
2006
IEEE
16 years 7 months ago
Discriminative cluster analysis
Clustering is one of the most widely used statistical tools for data analysis. Among all existing clustering techniques, k-means is a very popular method because of its ease of pr...
Fernando De la Torre, Takeo Kanade
SSDBM
2007
IEEE
110views Database» more  SSDBM 2007»
16 years 27 days ago
On Exploring Complex Relationships of Correlation Clusters
In high dimensional data, clusters often only exist in arbitrarily oriented subspaces of the feature space. In addition, these so-called correlation clusters may have complex rela...
Elke Achtert, Christian Böhm, Hans-Peter Krie...