PCA Extension and Correspondence Analysis  Publications of Chris Ding
Relationship between PCA and Kmeans Clustering
PCA and Extension
Adaptive Dimension Reduction

Adaptive Dimension Reduction for Clustering High Dimensional Data.
(Recursive projection to cluster centroid subspace instead of PCA subspace)
Chris Ding, Xiaofeng He, Hongyuan Zha, Horst Simon.
Proc. 2nd IEEE Int'l Conf. Data Mining, pp.147154, Dec. 2002. Maebashi, Japan.
( Postscript file)
Clustering and Ordering of bipartite graph (contingency table)
 Correspondence Analysis

Bipartite Graph Partitioning and Data Clustering,
(Simultaneous clustering of rows and columns of a rectangle
data matrix with a coherent objective function. We show
this twoway clustering is identical to Correspondence Analysis).
Hongyuan Zha, Xiaofeng He, Chris Ding, Ming Gu and Horst Simon.
Proc. of ACM 10th Int'l Conf. Information
and Knowledge Management (CIKM 2001), pp.2531, 2001, Atlanta, USA.
(
Postscript file)

Unsupervised feature selection via twoway ordering
in gene expression analysis
(Optimal two ordering and Correspondence Analysis)
Chris Ding.
Bioinformatics.
v.19, pp.12591266, 2003.
(Paper and supplimentary data)
From PCA to Scaled PCA, SelfAggregation

Document Retrieval and Clustering: from Principal Component Analysis to
Selfaggregation Networks.
(Refined objective functions for simultaneous clustering
of rows and columns of a rectangle data matrix using connectivity networks)
Chris Ding.
Proc. Int'l Parallel and Distributed Processing Symposium
Proceedings of 9th Int'l Workshop on Artificial Intelligence
and Statistics, January 2003, Key West, Florida, Eds.
C.M. Bishop and B.J. Frey (editors)
( ps file)

Data Clustering: Principal Components, Hopfield and SelfAggregation
Networks.
(Clustering objectives and solutions: evolution from the simple
to the sophisticated)
Chris Ding.
Proc. Int'l Joint Conf on Artificial Intelligence (IJCAI 2003),
pp.479484. August 2003
(
Postscript file)