Citations of Chris Ding's Publications
Citations tracked by Google Scholar:
"Chris Ding, Chris H.Q. Ding, H.Q.Ding"
My papers have been cited 26934 times (h-index 69)
(according to Google Scholar, as of May 15, 2017).
Some Significant Citations
Frequently Cited Papers
Feature Selection Based on Mutual Information:
Criteria of Max-dependency, Max-relevance, and Min-redundancy.
Hanchuan Peng, Fuhui Long, Chris Ding.
IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.27(8): 1226-1238 (2005)
(cited 479 times)
Multi-class Protein Fold Recognition Using Support Vector Machines and
(Paper and data)
(Protein 3D structure prediction)
Chris Ding and Inna Dubchak.
Bioinformatics, 2001, v.17, pp.349-358.
(cited 475 times)
A Min-Max Cut Algorithm for Graph Partitioning and Data Clustering,
Journal version PS )
(Spectral clustering that minimizes between-cluster similarities
and maximizes within-cluster similarities)
Chris Ding, Xiaofeng He, Hongyuan Zha, Ming Gu, and Horst D Simon.
Proc. IEEE Int'l Conf. Data Mining, pp.107-114. December 2001.
(cited 305+74 times)
Atomic Level Simulations of on a Million Particles: The Cell Multipole
Method for Coulomb and London Interactions.
(Molecular dynamics algorithm for computing protein structures)
H.Q. Ding, N. Karasawa and W.A. Goddard.
J. of Chemical Physics, vol.97, pp:4309-4315 (1992).
(cited 312 times)
Spectral Relaxation for K-means Clustering
(K-means clustering indicators are relaxed to principal components)
Hongyuan Zha, Chris Ding, Ming Gu, Xiaofeng He, and Horst D Simon.
Neural Information Processing Systems (NIPS 2001)
v.14, pp. 1057-1064, Dec. 2001.
(cited 225 times)
K-means Clustering via Principal Component Analysis.
(Show that the solution of K-means are given by PCA. Follow-up work on
Chris Ding and Xiaofeng He.
Proc. of Int'l Conf. Machine Learning (ICML 2004), pp 225-232. July 2004.
( PDF file)
(cited 216 times)
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 D. Simon.
Proc. ACM 10th Int'l Conf. Information and Knowledge Management (CIKM 2001),
pp.25-31, October 2001.
(cited 169 times)
On the Equivalence of Nonnegative Matrix Factorization
and Spectral Clustering.
Chris Ding, Xiaofeng He, and Horst D. Simon.
Proc. SIAM Int'l Conf. Data Mining, pp:606-610, April 2005.
(cited 144 times)
Orthogonal Nonnegative Matrix Tri-factorizations for Clustering
( PDF file)
Chris Ding, Tao Li, Wei Peng, Haesun Park.
Proc Int'l Conf. on Knowledge Discovery and Data Mining (KDD 2006),
(cited 117 times)
PageRank, HITS and a Unified Framework for Link Analysis.
( ps file)
(Combine mutual re-enforcement and link weight normalization into a
Chris Ding, Xiaofeng He, Parry Husbands, Hongyuan Zha, and Horst D. Simon
Proc. of 25th ACM SIGIR Conf. 2002.
(cited 104 times)
A Similarity-based Probability Model for Latent Semantic Indexing.
( ps file)
(Show LSI is optimal maximum-likelihood solutions
to a probabilistic generative model)
Proc. ACM SIGIR 1999, pp:59-65. August 1999.
(cited 110 times)
Adaptive Dimension Reduction for Clustering High Dimensional Data.
Chris Ding, Xiaofeng He, Hongyuan Zha, and Horst D. Simon.
Proc. IEEE Int'l Conf. Data Mining, pp.147-154, Dec. 2002.
(cited 96 times)