Spectral Clustering

Publications of Chris H.Q. Ding
Spectral Relaxation of Kmeans Clustering  Equivalence to PCA

Spectral Relaxation for Kmeans Clustering
(Cluster indicators for Kmeans relax to principal components)
Hongyuan Zha, Chris Ding, Ming Gu, Xiaofeng He and Horst Simon.
Neural Information Processing Systems vol.14 (NIPS 2001).
pp. 10571064, Vancouver, Canada. Dec. 2001.
(
Postscript file)

Kmeans Clustering via Principal Component Analysis.
(Equivalence of Kmeans and PCA)
Chris Ding and Xiaofeng He.
Proc. of Int'l Conf. Machine Learning (ICML 2004), pp 225232. July 2004.
( PDF file,
PS file)
Graph Laplacian Based Spectral Clustering

A MinMax Cut for Graph Partitioning and Data Clustering,
(Spectral clustering that minimizes betweencluster similarities
and maximizes withincluster similarities)
Chris Ding, Xiaofeng He, Hongyuan Zha, Ming Gu and Horst Simon.
Proc. of 1st IEEE Int'l Conf. Data Mining. San Jose, CA, 2001. pp.107114.
(
Conference paper PS file,
Journal version PS file)

A Spectral Method to Separate Disconnected and Nearlydisconnected
Web Graph Components.
(Perturbation analysis of the Laplacian matrix and spectral clustering objective functions)
Chris Ding, Xiaofeng He and Hongyuan Zha.
Proc 7th Int'l Conf. on Knowledge Discovery and Data Mining (KDD 2001)
pp.275280, August 2001.
(
Postscript file)

Spectral Relaxation Models and Structure Analysis for Kway Graph Clustering and Biclustering.
(Spectral relaxation of Multiway Normalized Cut and MinMaxCut)
Ming Gu, Hongyuan Zha, Chris Ding, Xiaofeng He and Horst Simon. Technical Report, 2001.
(
Postscript file)

Unsupervised Learning: Selfaggregation in Scaled Principal Component Space.
(Selfaggregation in Laplacian eigenspace and
connectivity networks for cluster structure identification)
C. Ding, X. He, Hongyuan Zha, and H. Simon.
6th European Conference on Principles of Data Mining and Knowledge Discovery (PKDD 2002),
T. Elomaa, H. Mannila, H. Toivonen (Eds.), Lecture Notes in
Artificial Intelligence, Vol. 2431, pp. 112124.
(
PDF file)

Linearized Cluster Assignment via Spectral Ordering
(Reduce multiway spectral clustering to 1D clustering)
Chris Ding and Xiaofeng He.
Proc. of Int'l Conf. Machine Learning (ICML 2004), pp.233240. July 2004.
( PDF file,
PS file)
Spectral Clustering of Bipartite Graphs

Bipartite Graph Partitioning and Data Clustering,
(Simultaneous clustering of rows and columns of a rectangle
data matrix with a coherent objective function)
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)

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.
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)
( PDF 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)