Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Min-max Cut Algorithm for Graph Partitioning and Data Clustering
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Approximating the Cut-Norm via Grothendieck's Inequality
SIAM Journal on Computing
A tutorial on spectral clustering
Statistics and Computing
Statistical Analysis of Network Data: Methods and Models
Statistical Analysis of Network Data: Methods and Models
L1-norm projection pursuit principal component analysis
Computational Statistics & Data Analysis
New spectral methods for ratio cut partitioning and clustering
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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We consider correspondence analysis (CA) and taxicab correspondence analysis (TCA) of relational datasets that can mathematically be described as weighted loopless graphs. Such data appear in particular in network analysis. We present CA and TCA as relaxation methods for the graph partitioning problem. Examples of real datasets are provided.