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» Algorithms for the Sample Mean of Graphs
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NIPS
2008
15 years 1 months ago
On the Reliability of Clustering Stability in the Large Sample Regime
Clustering stability is an increasingly popular family of methods for performing model selection in data clustering. The basic idea is that the chosen model should be stable under...
Ohad Shamir, Naftali Tishby
BIOCOMP
2007
15 years 1 months ago
Learning Node Replacement Graph Grammars in Metabolic Pathways
— This paper describes graph-based relational, unsupervised learning algorithm to infer node replacement graph grammar and its application to metabolic pathways. We search for fr...
Jacek P. Kukluk, Chang Hun You, Lawrence B. Holder...
GECCO
2006
Springer
207views Optimization» more  GECCO 2006»
15 years 3 months ago
Both robust computation and mutation operation in dynamic evolutionary algorithm are based on orthogonal design
A robust dynamic evolutionary algorithm (labeled RODEA), where both the robust calculation and mutation operator are based on an orthogonal design, is proposed in this paper. Prev...
Sanyou Y. Zeng, Rui Wang, Hui Shi, Guang Chen, Hug...
CVPR
2012
IEEE
13 years 2 months ago
Non-negative low rank and sparse graph for semi-supervised learning
Constructing a good graph to represent data structures is critical for many important machine learning tasks such as clustering and classification. This paper proposes a novel no...
Liansheng Zhuang, Haoyuan Gao, Zhouchen Lin, Yi Ma...
CSB
2003
IEEE
150views Bioinformatics» more  CSB 2003»
15 years 5 months ago
Algorithms for Bounded-Error Correlation of High Dimensional Data in Microarray Experiments
The problem of clustering continuous valued data has been well studied in literature. Its application to microarray analysis relies on such algorithms as -means, dimensionality re...
Mehmet Koyutürk, Ananth Grama, Wojciech Szpan...