Chris H. Q. Ding

发表

The Relationships Among Various Nonnegative Matrix Factorization Methods for Clustering

Tao Li, Chris H. Q. Ding, C. Ding, 2006, Sixth International Conference on Data Mining (ICDM'06).

Minimum Redundancy Feature Selection from Microarray Gene Expression Data

Chris H. Q. Ding, Hanchuan Peng, C. Ding, 2005, J. Bioinform. Comput. Biol..

A Nonnegative Locally Linear KNN model for image recognition

Chris H. Q. Ding, Bin Luo, Sibao Chen, 2018, Pattern Recognit..

Non-negative Tri-factor tensor decomposition with applications

Chris H. Q. Ding, Tao Li, Zhongyuan Zhang, 2012, Knowledge and Information Systems.

PCA-guided search for K-means

Chris H. Q. Ding, Qin Xu, Bin Luo, 2015, Pattern Recognit. Lett..

Tensor Fold-in Algorithms for Social Tagging Prediction

Chris H. Q. Ding, Miao Zhang, Zhifang Liao, 2011, 2011 IEEE 11th International Conference on Data Mining.

Simultaneous tensor subspace selection and clustering: the equivalence of high order svd and k-means clustering

Chris H. Q. Ding, Heng Huang, Tao Li, 2008, KDD.

A Probabilistic Approach for Optimizing Spectral Clustering

Chris H. Q. Ding, Rong Jin, Feng Kang, 2005, NIPS.

Uncorrelated Lasso

Chris H. Q. Ding, Ying Xie, Bin Luo, 2013, AAAI.

Multi-Label Classification: Inconsistency and Class Balanced K-Nearest Neighbor

Chris H. Q. Ding, Hua Wang, Heng Huang, 2010, AAAI.

Low-Rank Matrix Recovery via Efficient Schatten p-Norm Minimization

Feiping Nie, Chris H. Q. Ding, Heng Huang, 2012, AAAI.

Contraction graphs for representation and analysis of RNA secondary structure

Chris H. Q. Ding, Xiaofeng He, Richard F. Meraz, 2004, Proceedings. 2004 IEEE Computational Systems Bioinformatics Conference, 2004. CSB 2004..

Cluster Indicator Decomposition for Efficient Matrix Factorization

Chris H. Q. Ding, Heng Huang, Dijun Luo, 2011, IJCAI.

On the equivalence between Non-negative Matrix Factorization and Probabilistic Latent Semantic Indexing

Chris H. Q. Ding, Wei Peng, Tao Li, 2008, Comput. Stat. Data Anal..

Robust Integrated Locally Linear Embedding

Chris H. Q. Ding, Ying Xie, Jin Tang, 2012, CCBR.

Predicting Protein-Protein Interactions from Multimodal Biological Data Sources via Nonnegative Matrix Tri-Factorization

Feiping Nie, Chris H. Q. Ding, Hua Wang, 2012, RECOMB.

Bipartite graph partitioning and data clustering

Chris H. Q. Ding, Hongyuan Zha, Xiaofeng He, 2001, CIKM '01.

NMF and PLSI: equivalence and a hybrid algorithm

Chris H. Q. Ding, Wei Peng, Tao Li, 2006, SIGIR '06.

Convex and Semi-Nonnegative Matrix Factorizations

Chris H. Q. Ding, Michael I. Jordan, Tao Li, 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

KDD2009 workshop report DMMT'09: data mining using matrices and tensors

Chris H. Q. Ding, Tao Li, 2010, SKDD.

Structure search and stability enhancement of Bayesian networks

Chris H. Q. Ding, Hanchuan Peng, C. Ding, 2003, Third IEEE International Conference on Data Mining.

Binary matrix factorization for analyzing gene expression data

Chris H. Q. Ding, Tao Li, Zhongyuan Zhang, 2009, Data Mining and Knowledge Discovery.

Non-Convex Feature Learning via L_{p, inf} Operator

Chris H. Q. Ding, Deguang Kong, 2014, AAAI.

A Semi-definite Positive Linear Discriminant Analysis and Its Applications

Chris H. Q. Ding, Deguang Kong, 2012, 2012 IEEE 12th International Conference on Data Mining.

Supernova Recognition Using Support Vector Machines

Chris H. Q. Ding, Cecilia R. Aragon, Raquel A. Romano, 2006, 2006 5th International Conference on Machine Learning and Applications (ICMLA'06).

Label Propagation on K-partite Graphs

Chris H. Q. Ding, Tao Li, Dingding Wang, 2009, 2009 International Conference on Machine Learning and Applications.

MPI and OpenMP Paradigms on Cluster of SMP Architectures: The Vacancy Tracking Algorithm for Multi-Dimensional Array Transposition

Chris H. Q. Ding, Yun He, C. Ding, 2002, ACM/IEEE SC 2002 Conference (SC'02).

High Performance Fortran for practical scientific algorithms: An up-to-date evaluation

Chris H. Q. Ding, 1999, Future Gener. Comput. Syst..

A learning framework using Green's function and kernel regularization with application to recommender system

Chris H. Q. Ding, Rong Jin, Tao Li, 2007, KDD '07.

Symmetric two dimensional linear discriminant analysis (2DLDA)

Chris H. Q. Ding, Heng Huang, Dijun Luo, 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

Toward structural sparsity: an explicit $$\ell _{2}/\ell _0$$ approach

Chris H. Q. Ding, Heng Huang, Dijun Luo, 2013, 2010 IEEE International Conference on Data Mining.

Supervised and Projected Sparse Coding for Image Classification

Feiping Nie, Chris H. Q. Ding, Heng Huang, 2013, AAAI.

Graph Convolutional Network Based on Manifold Similarity Learning

Qiang Li, Chris H. Q. Ding, Hao Huang, 2020, Cogn. Comput..

Image annotation using multi-label correlated Green's function

Chris H. Q. Ding, Hua Wang, Heng Huang, 2009, 2009 IEEE 12th International Conference on Computer Vision.

PageRank, HITS and a unified framework for link analysis

Chris H. Q. Ding, Hongyuan Zha, Xiaofeng He, 2002, SIGIR '02.

Integrating Clustering and Multi-Document Summarization by Bi-Mixture Probabilistic Latent Semantic Analysis (PLSA) with Sentence Bases

Chris H. Q. Ding, Tao Li, Chao Shen, 2011, AAAI.

Climate Data Assimilation on a Massively Parallel Supercomputer

Chris H. Q. Ding, Robert D. Ferraro, 1996, Proceedings of the 1996 ACM/IEEE Conference on Supercomputing.

Integrating Symmetric Nonnegative Matrix Factorization and Normalized Cut Spectral Clustering

Chris H. Q. Ding, Zhichen Xia, 2010, 2010 IEEE International Conference on Data Mining Workshops.

Probabilistic solutions of influence propagation on social networks

Enhong Chen, Chris H. Q. Ding, Miao Zhang, 2013, CIKM.

Function-Function Correlated Multi-label Protein Function Prediction over Interaction Networks

Chris H. Q. Ding, Hua Wang, Heng Huang, 2013, J. Comput. Biol..

Cluster merging and splitting in hierarchical clustering algorithms

Chris H. Q. Ding, Xiaofeng He, C. Ding, 2002, 2002 IEEE International Conference on Data Mining, 2002. Proceedings..

Posterior probabilistic clustering using NMF

Chris H. Q. Ding, Wei Peng, Tao Li, 2008, SIGIR '08.

An element-based concurrent partitioner for unstructured finite element meshes

Chris H. Q. Ding, Robert D. Ferraro, 1996, Proceedings of International Conference on Parallel Processing.

Community discovery using nonnegative matrix factorization

Fei Wang, Chris H. Q. Ding, Shenghuo Zhu, 2011, Data Mining and Knowledge Discovery.

Binary Matrix Factorization with Applications

Chris H. Q. Ding, Tao Li, Zhongyuan Zhang, 2007, Seventh IEEE International Conference on Data Mining (ICDM 2007).

Minimum redundancy feature selection from microarray gene expression data

Chris H. Q. Ding, Hanchuan Peng, C. Ding, 2003, Computational Systems Bioinformatics. CSB2003. Proceedings of the 2003 IEEE Bioinformatics Conference. CSB2003.

Regularized Singular Value Decomposition and Application to Recommender System pdf

Feiping Nie, Chris H. Q. Ding, Shuai Zheng, 2018, ArXiv.

Sparse multi-task regression and feature selection to identify brain imaging predictors for memory performance

Shannon L. Risacher, Andrew J. Saykin, Feiping Nie, 2011, 2011 International Conference on Computer Vision.

Nonnegative matrix factorization using a robust error function

Chris H. Q. Ding, Deguang Kong, C. Ding, 2012, 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Kernel Alignment Inspired Linear Discriminant Analysis pdf

Chris H. Q. Ding, Shuai Zheng, 2014, ECML/PKDD.

Positive sample only learning (PSOL) for predicting RNA genes in E. coli

Chris H. Q. Ding, Xiaofeng He, Richard F. Meraz, 2004, Proceedings. 2004 IEEE Computational Systems Bioinformatics Conference, 2004. CSB 2004..

Weighted Feature Subset Non-negative Matrix Factorization and Its Applications to Document Understanding

Chris H. Q. Ding, Tao Li, Dingding Wang, 2010, 2010 IEEE International Conference on Data Mining.

Active Learning for Support Vector Machines with Maximum Model Change

Chris H. Q. Ding, Wenbin Cai, Ya Zhang, 2014, ECML/PKDD.

Robust Matrix Completion via Joint Schatten p-Norm and lp-Norm Minimization

Feiping Nie, Chris H. Q. Ding, Hua Wang, 2012, 2012 IEEE 12th International Conference on Data Mining.

Angular Decomposition

Chris H. Q. Ding, Jin Tang, Bin Luo, 2011, IJCAI.

Efficient Algorithms for Selecting Features with Arbitrary Group Constraints via Group Lasso

Chris H. Q. Ding, Deguang Kong, C. Ding, 2013, 2013 IEEE 13th International Conference on Data Mining.

Linear Discriminant Analysis: New Formulations and Overfit Analysis

Chris H. Q. Ding, Heng Huang, Dijun Luo, 2011, AAAI.

Weighted Consensus Clustering

Chris H. Q. Ding, Tao Li, C. Ding, 2008, SDM.

Simultaneous clustering of multi-type relational data via symmetric nonnegative matrix tri-factorization

Chris H. Q. Ding, Hua Wang, Heng Huang, 2011, CIKM '11.

Tensor reduction error analysis — Applications to video compression and classification

Chris H. Q. Ding, Heng Huang, Dijun Luo, 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

A Harmonic Mean Linear Discriminant Analysis for Robust Image Classification

Feiping Nie, Chris H. Q. Ding, Heng Huang, 2016, 2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI).

Knowledge transformation from word space to document space

Chris H. Q. Ding, Tao Li, Yi Zhang, 2008, SIGIR '08.

Extended adaptive Lasso for multi-class and multi-label feature selection

Chris H. Q. Ding, Jian Zhang, Bin Luo, 2019, Knowl. Based Syst..

Identification of Functional Modules in Protein Complexes via Hyperclique Pattern Discovery

Hui Xiong, Chris H. Q. Ding, Vipin Kumar, 2004, Pacific Symposium on Biocomputing.

Closed form solution of similarity algorithms

Chris H. Q. Ding, Miao Zhang, Sharma Chakravarthy, 2010, SIGIR '10.

Principal Component Analysis and Effective K-Means Clustering

Chris H. Q. Ding, Xiaofeng He, C. Ding, 2004, SDM.

Joint Schatten $$p$$p-norm and $$\ell _p$$ℓp-norm robust matrix completion for missing value recovery

Feiping Nie, Chris H. Q. Ding, Hua Wang, 2013, Knowledge and Information Systems.

Cluster Structure of K-means Clustering via Principal Component Analysis

Chris H. Q. Ding, Xiaofeng He, C. Ding, 2004, PAKDD.

A probabilistic model for Latent Semantic Indexing

Chris H. Q. Ding, C. Ding, 2005, J. Assoc. Inf. Sci. Technol..

High Performance Computations for Large Scale Simulations of Subsurface Multiphase Fluid and Heat Flow

Erik Elmroth, Chris H. Q. Ding, Yu-Shu Wu, 2004, The Journal of Supercomputing.

Web document clustering using hyperlink structures

Chris H. Q. Ding, Hongyuan Zha, Xiaofeng He, 2001, Comput. Stat. Data Anal..

Atmosperic Data Assimilation on Distributed-Memory Parallel Supercomputers

Chris H. Q. Ding, Jay Walter Larson, Jing Guo, 1998, HPCN Europe.

Exclusive Feature Learning on Arbitrary Structures via \ell_{1, 2}-norm

Feiping Nie, Chris H. Q. Ding, Ji Liu, 2014, NIPS.

Multi-Class L2,1-Norm Support Vector Machine

Feiping Nie, Chris H. Q. Ding, Heng Huang, 2011, 2011 IEEE 11th International Conference on Data Mining.

Coupling Multicomponent Models with MPH on Distributed Memory Computer Architectures

Chris H. Q. Ding, Yun He, C. Ding, 2005, Int. J. High Perform. Comput. Appl..

Dynamic cluster formation using level set methods

Chris H. Q. Ding, Andy M. Yip, Tony F. Chan, 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

A Portable 3D FFT Package for Distributed-Memory Parallel Architectures

Chris H. Q. Ding, Donald B. Gennery, Robert D. Ferraro, 1995, PPSC.

Slices: A Scalable Partitioner for Finite Element Meshes

Chris H. Q. Ding, Robert D. Ferraro, 1995, PPSC.

Nonnegative Lagrangian Relaxation of K-Means and Spectral Clustering

Chris H. Q. Ding, Xiaofeng He, Horst D. Simon, 2005, ECML.

Social Trust Prediction Using Rank-k Matrix Recovery

Feiping Nie, Chris H. Q. Ding, Heng Huang, 2013, IJCAI.

Multi-label Feature Transform for Image Classifications

Chris H. Q. Ding, Hua Wang, Heng Huang, 2010, ECCV.

An algorithm framework of sparse minimization for positive definite quadratic forms

Chris H. Q. Ding, Bin Luo, Sibao Chen, 2015, Neurocomputing.

Enhancing Collaborative Filtering by User Interest Expansion via Personalized Ranking

Hui Xiong, Enhong Chen, Qi Liu, 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

Parallelization with Multiplicative Algorithms for Big Data Mining

Chris H. Q. Ding, Heng Huang, Dijun Luo, 2012, 2012 IEEE 12th International Conference on Data Mining.

Active Learning for Classification with Maximum Model Change

Chris H. Q. Ding, Wenbin Cai, Ya Zhang, 2017, ACM Trans. Inf. Syst..

Image Categorization Using Directed Graphs

Chris H. Q. Ding, Hua Wang, Heng Huang, 2010, ECCV.

Accelerating Deep Learning with Shrinkage and Recall

Chris H. Q. Ding, Abhinav Vishnu, Shuai Zheng, 2016, 2016 IEEE 22nd International Conference on Parallel and Distributed Systems (ICPADS).

2-Dimensional Singular Value Decomposition for 2D Maps and Images

Chris H. Q. Ding, Jieping Ye, C. Ding, 2005, SDM.

Finding Hotspots in Document Collection

Chris H. Q. Ding, Wei Peng, Tao Li, 2007, 19th IEEE International Conference on Tools with Artificial Intelligence(ICTAI 2007).

Multi-Subspace Representation and Discovery

Feiping Nie, Chris H. Q. Ding, Heng Huang, 2011, ECML/PKDD.

Guest editorial: special issue on data mining with matrices, graphs and tensors

Fei Wang, Chris H. Q. Ding, Tao Li, 2011, Data Mining and Knowledge Discovery.

Towards Structural Sparsity: An Explicit l2/l0 Approach

Chris H. Q. Ding, Heng Huang, Dijun Luo, 2010, ICDM.

Robust nonnegative matrix factorization using L21-norm

Chris H. Q. Ding, Heng Huang, Deguang Kong, 2011, CIKM '11.

Semi-Supervised Remote Sensing Image Semantic Segmentation via Consistency Regularization and Average Update of Pseudo-Label

Chris H. Q. Ding, Bin Luo, Sibao Chen, 2020, Remote. Sens..

On Trivial Solution and Scale Transfer Problems in Graph Regularized NMF

Chris H. Q. Ding, Jiawei Han, Quanquan Gu, 2011, IJCAI.

Chris H. Q. Ding, Hua Wang, Heng Huang, 2014, RECOMB.

Infobox suggestion for Wikipedia entities

Chris H. Q. Ding, Ashis Kumer Biswas, Chengkai Li, 2012, CIKM '12.

A multi-level approach to SCOP fold recognition

Srinivasan Parthasarathy, Keith Marsolo, Chris H. Q. Ding, 2005, Fifth IEEE Symposium on Bioinformatics and Bioengineering (BIBE'05).

Multi-document summarization via sentence-level semantic analysis and symmetric matrix factorization

Chris H. Q. Ding, Shenghuo Zhu, Tao Li, 2008, SIGIR '08.

Evaluations of HPF for Practical Scientific Algorithms on T3E

Chris H. Q. Ding, 1998, HPCN Europe.

Robust Principal Component Analysis with Non-Greedy l1-Norm Maximization

Feiping Nie, Chris H. Q. Ding, Hua Wang, 2011, IJCAI.

K-means clustering via principal component analysis

Chris H. Q. Ding, Xiaofeng He, C. Ding, 2004, ICML.

K-nearest-neighbor consistency in data clustering: incorporating local information into global optimization

Chris H. Q. Ding, Xiaofeng He, C. Ding, 2004, SAC '04.

Multi-Level Cluster Indicator Decompositions of Matrices and Tensors

Chris H. Q. Ding, Heng Huang, Dijun Luo, 2011, AAAI.

Dyadic transfer learning for cross-domain image classification

Feiping Nie, Chris H. Q. Ding, Hua Wang, 2011, 2011 International Conference on Computer Vision.

Data Organization and I/O in a Parallel Ocean Circulation Model

Chris H. Q. Ding, Yun He, 1999, SC.

On the eigenvectors of p-Laplacian

Feiping Nie, Chris H. Q. Ding, Heng Huang, 2010, Machine Learning.

Towards a bridge between cost and wealth in risk-aware planning

Fillia Makedon, Chris H. Q. Ding, Yong Lin, 2011, Applied Intelligence.

Nonnegative Matrix Factorization for Combinatorial Optimization: Spectral Clustering, Graph Matching, and Clique Finding

Chris H. Q. Ding, Michael I. Jordan, Tao Li, 2008, 2008 Eighth IEEE International Conference on Data Mining.

Collective Kernel Construction in Noisy Environment

Chris H. Q. Ding, Miao Zhang, Deguang Kong, 2013, SDM.

Exploiting user interests for collaborative filtering: interests expansion via personalized ranking

Hui Xiong, Enhong Chen, Qi Liu, 2010, CIKM '10.

Adaptive Loss Minimization for Semi-Supervised Elastic Embedding

Feiping Nie, Chris H. Q. Ding, Hua Wang, 2013, IJCAI.

Image annotation using bi-relational graph of images and semantic labels

Chris H. Q. Ding, Hua Wang, Heng Huang, 2011, CVPR 2011.

Integrating program component executables on distributed memory architectures via MPH

Chris H. Q. Ding, Yun He, C. Ding, 2004, 18th International Parallel and Distributed Processing Symposium, 2004. Proceedings..

Discriminant Laplacian Embedding

Chris H. Q. Ding, Hua Wang, Heng Huang, 2010, AAAI.

Forging The Graphs: A Low Rank and Positive Semidefinite Graph Learning Approach

Feiping Nie, Chris H. Q. Ding, Heng Huang, 2012, NIPS.

Linear regression based projections for dimensionality reduction

Chris H. Q. Ding, Bin Luo, Sibao Chen, 2018, Inf. Sci..

Predicting Protein-Protein Interactions from Multimodal Biological Data Sources via Nonnegative Matrix Tri-Factorization

Feiping Nie, Chris H. Q. Ding, Hua Wang, 2012, RECOMB.

Function-Function Correlated Multi-Label Protein Function Prediction over Interaction Networks

Chris H. Q. Ding, Hua Wang, Heng Huang, 2012, RECOMB.

KDD2008 workshop report DMMT'08: data mining using matrices and tensors

Chris H. Q. Ding, Shenghuo Zhu, Tao Li, 2008, SKDD.

Dynamic Cluster Formation Using Level Set Methods

Chris H. Q. Ding, Andy M. Yip, Tony F. Chan, 2005, PAKDD.

Modeling reliability for wireless sensor node coverage in assistive testbeds

Eric Becker, Fillia Makedon, Chris H. Q. Ding, 2010, PETRA '10.

Heterogeneous Visual Features Fusion via Sparse Multimodal Machine

Feiping Nie, Chris H. Q. Ding, Hua Wang, 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

Robust Tucker Tensor Decomposition for Effective Image Representation

Chris H. Q. Ding, Miao Zhang, C. Ding, 2013, 2013 IEEE International Conference on Computer Vision.

Directed Graph Learning via High-Order Co-linkage Analysis

Chris H. Q. Ding, Hua Wang, Heng Huang, 2010, ECML/PKDD.

Hierarchical Ensemble Clustering

Chris H. Q. Ding, Tao Li, Li Zheng, 2010, 2010 IEEE International Conference on Data Mining.

Efficient Parallel I/O in Community Atmosphere Model (CAM)

Chris H. Q. Ding, Yu-heng Tseng, C. Ding, 2008, Int. J. High Perform. Comput. Appl..

PageRank, HITS and a unified framework for link analysis

Chris H. Q. Ding, Hongyuan Zha, Xiaofeng He, 2002, SIGIR '02.

Using Accurate Arithmetics to Improve Numerical Reproducibility and Stability in Parallel Applications

Chris H. Q. Ding, Yun He, C. Ding, 2000, ICS '00.

Pairwise-Covariance Linear Discriminant Analysis

Chris H. Q. Ding, Deguang Kong, C. Ding, 2014, AAAI.

Saliency Detection via A Graph Based Diffusion Model

Chris H. Q. Ding, Bo Jiang, Bin Luo, 2017, GbRPR.

Protein Function Prediction via Laplacian Network Partitioning Incorporating Function Category Correlations

Chris H. Q. Ding, Hua Wang, Heng Huang, 2013, IJCAI.

Consensus group stable feature selection

Chris H. Q. Ding, Lei Yu, Steven Loscalzo, 2009, KDD.

Are Tensor Decomposition Solutions Unique? On the Global Convergence HOSVD and ParaFac Algorithms pdf

Chris H. Q. Ding, Dijun Luo, Heng Huang, 2009, PAKDD.

Symmetric Nonnegative Matrix Factorization for Graph Clustering

Chris H. Q. Ding, Haesun Park, Da Kuang, 2012, SDM.

Chris H. Q. Ding, Hua Wang, Heng Huang, 2014, RECOMB.

Low-order tensor decompositions for social tagging recommendation

Chris H. Q. Ding, Miao Zhang, Sharma Chakravarthy, 2011, WSDM '11.

Robust Out-of-Sample Data Recovery

Chris H. Q. Ding, Bo Jiang, Bin Luo, 2016, IJCAI.

Dimension Reduction Techniques for Clustering

Chris H. Q. Ding, 2009, Encyclopedia of Database Systems.

Joint stage recognition and anatomical annotation of drosophila gene expression patterns

Chris H. Q. Ding, Hua Wang, Heng Huang, 2012, Bioinform..

On the Equivalence of Nonnegative Matrix Factorization and Spectral Clustering

Chris H. Q. Ding, Xiaofeng He, C. Ding, 2005, SDM.

Monte Carlo simulations of quantum systems on massively parallel supercomputers

Chris H. Q. Ding, C. Ding, 1993, Supercomputing '93. Proceedings.

Weighted Feature Subset Non-negative Matrix Factorization and Its Applications to Document Understanding

Chris H. Q. Ding, Tao Li, Dingding Wang, 2010, ICDM.

Non-negative Laplacian Embedding

Chris H. Q. Ding, Heng Huang, Tao Li, 2009, 2009 Ninth IEEE International Conference on Data Mining.

Orthogonal nonnegative matrix t-factorizations for clustering

Chris H. Q. Ding, Wei Peng, Tao Li, 2006, KDD '06.

Term norm distribution and its effects on Latent Semantic Indexing

Chris H. Q. Ding, Horst D. Simon, Parry Husbands, 2005, Inf. Process. Manag..

Gaussian Process for Recommender Systems

Enhong Chen, Qi Liu, Chris H. Q. Ding, 2011, KSEM.

A Framework for Hierarchical Ensemble Clustering

Tao Li, Chris H. Q. Ding, Li Zheng, 2014, TKDD.

Analysis of gene expression profiles: class discovery and leaf ordering

Chris H. Q. Ding, C. Ding, 2002, RECOMB '02.

A spectral method to separate disconnected and nearly-disconnected web graph components

Chris H. Q. Ding, Hongyuan Zha, Xiaofeng He, 2001, KDD '01.

Rank Ordering Constraints Elimination with Application for Kernel Learning

Yihong Gong, Chris H. Q. Ding, Zongze Wu, 2017, AAAI.

Extended linear regression for undersampled face recognition

Chris H. Q. Ding, Bin Luo, Sibao Chen, 2014, J. Vis. Commun. Image Represent..

Graph Evolution via Social Diffusion Processes

Chris H. Q. Ding, Heng Huang, Dijun Luo, 2011, ECML/PKDD.

Maximum Margin Multi-Instance Learning

Feiping Nie, Chris H. Q. Ding, Hua Wang, 2011, NIPS.

Consensus spectral clustering in near-linear time

Feiping Nie, Chris H. Q. Ding, Heng Huang, 2011, 2011 IEEE 27th International Conference on Data Engineering.

Determining modular organization of protein interaction networks by maximizing modularity density

Chris H. Q. Ding, Shi-Hua Zhang, Xiang-Sun Zhang, 2010, BMC Systems Biology.

Network community discovery: solving modularity clustering via normalized cut

Chris H. Q. Ding, Linbin Yu, C. Ding, 2010, MLG '10.

Nonnegative Matrix Tri-factorization Based High-Order Co-clustering and Its Fast Implementation

Feiping Nie, Chris H. Q. Ding, Hua Wang, 2011, 2011 IEEE 11th International Conference on Data Mining.

Early Active Learning via Robust Representation and Structured Sparsity

Feiping Nie, Chris H. Q. Ding, Hua Wang, 2013, IJCAI.

Minimal Shrinkage for Noisy Data Recovery Using Schatten-p Norm Objective

Chris H. Q. Ding, Miao Zhang, Deguang Kong, 2013, ECML/PKDD.

Selective Labeling via Error Bound Minimization

Chris H. Q. Ding, Jiawei Han, Tong Zhang, 2012, NIPS.

Parallel Algorithms for 1D FFTs on Real Numbers

Chris H. Q. Ding, 1999, PPSC.

Cluster Aggregate Inequality and Multi-level Hierarchical Clustering

Chris H. Q. Ding, Xiaofeng He, 2005, PKDD.

Cauchy Graph Embedding

Feiping Nie, Chris H. Q. Ding, Heng Huang, 2011, ICML.

Adaptive dimension reduction for clustering high dimensional data

Chris H. Q. Ding, Hongyuan Zha, Xiaofeng He, 2002, 2002 IEEE International Conference on Data Mining, 2002. Proceedings..

Robust tensor factorization using R1 norm

Chris H. Q. Ding, Heng Huang, C. Ding, 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

Finding cliques in protein interaction networks via transitive closure of a weighted graph

Chris H. Q. Ding, Hanchuan Peng, Xiaofeng He, 2005, BIOKDD.

Spectral Relaxation for K-means Clustering

Chris H. Q. Ding, Hongyuan Zha, Xiaofeng He, 2001, NIPS.

An Optimal Index Reshuffle Algorithm for Multidimensional Arrays and Its Applications for Parallel Architectures

Chris H. Q. Ding, C. Ding, 2001, IEEE Trans. Parallel Distributed Syst..

Cross-language web page classification via dual knowledge transfer using nonnegative matrix tri-factorization

Feiping Nie, Chris H. Q. Ding, Hua Wang, 2011, SIGIR.

Feature Selection at the Discrete Limit

Feiping Nie, Chris H. Q. Ding, Miao Zhang, 2014, AAAI.

An Efficient Algorithm for Feature Selection with Feature Correlation

Chris H. Q. Ding, Jin Tang, Bin Luo, 2012, IScIDE.

Parallel Computing at the NASA Data Assimilation Office (DAO)

Chris H. Q. Ding, Jing Guo, J. W. Larson, 1997, SC.

Multi-class protein fold recognition using support vector machines and neural networks

Chris H. Q. Ding, Inna Dubchak, C. Ding, 2001, Bioinform..

Linearized cluster assignment via spectral ordering

Chris H. Q. Ding, Xiaofeng He, C. Ding, 2004, ICML.

Unsupervised Feature Selection Via Two-way Ordering in Gene Expression Analysis

Chris H. Q. Ding, C. Ding, 2003, Bioinform..

Automatic topic identification using webpage clustering

Chris H. Q. Ding, Hongyuan Zha, Xiaofeng He, 2001, Proceedings 2001 IEEE International Conference on Data Mining.

Biclustering Protein Complex Interactions with a Biclique Finding Algorithm

Chris H. Q. Ding, Ya Zhang, Tao Li, 2006, Sixth International Conference on Data Mining (ICDM'06).

Large-Scale Network Representation Learning Based on Improved Louvain Algorithm and Deep Autoencoder

Chris H. Q. Ding, Bin Luo, Sibao Chen, 2020, PRCV.

Inferring disease associations of the long non-coding RNAs through non-negative matrix factorization

Chris H. Q. Ding, Ashis Kumer Biswas, Baoju Zhang, 2015, Network Modeling Analysis in Health Informatics and Bioinformatics.

Evolving Feature Selection

Chris H. Q. Ding, Hanchuan Peng, Fuhui Long, 2005, IEEE Intell. Syst..

A Closed Form Solution to Multi-View Low-Rank Regression

Feiping Nie, Chris H. Q. Ding, Heng Huang, 2015, AAAI.

Nonnegative Matrix Factorizations for Clustering: A Survey

Chris H. Q. Ding, Tao Li, C. Ding, 2018, Data Clustering: Algorithms and Applications.

Using accurate arithmetics to improve numerical reproducibility and stability in parallel applications

Chris H. Q. Ding, Yun He, 2000, ICS '00.

An Evaluation of MPI and OpenMP Paradigms for Multi-Dimensional Data Remapping

Chris H. Q. Ding, Yun He, 2002, WOMPAT.

Collaborative Filtering: Weighted Nonnegative Matrix Factorization Incorporating User and Item Graphs

Chris H. Q. Ding, Quanquan Gu, Jie Zhou, 2010, SDM.

CPL6: The New Extensible, High Performance Parallel Coupler for the Community Climate System Model

Chris H. Q. Ding, Yun He, Jay Walter Larson, 2005, Int. J. High Perform. Comput. Appl..

Robust Kernel Nonnegative Matrix Factorization

Chris H. Q. Ding, Edmond Chow, Zhichen Xia, 2012, 2012 IEEE 12th International Conference on Data Mining Workshops.

Knowledge transformation for cross-domain sentiment classification

Chris H. Q. Ding, Tao Li, Yi Zhang, 2009, SIGIR.

Exercise-Enhanced Sequential Modeling for Student Performance Prediction

Enhong Chen, Qi Liu, Chris H. Q. Ding, 2018, AAAI.

A min-max cut algorithm for graph partitioning and data clustering

Chris H. Q. Ding, Hongyuan Zha, Xiaofeng He, 2001, Proceedings 2001 IEEE International Conference on Data Mining.

A ghost cell expansion method for reducing communications in solving PDE problems

Chris H. Q. Ding, Yun He, C. Ding, 2001, SC.

An efficient algorithm for L1-norm principal component analysis

Chris H. Q. Ding, Miao Zhang, Linbin Yu, 2012, 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

PSoL: a positive sample only learning algorithm for finding non-coding RNA genes

Chris H. Q. Ding, Chunlin Wang, Richard F. Meraz, 2006, Bioinform..

Simultaneous Image Classification and Annotation via Biased Random Walk on Tri-relational Graph

Chris H. Q. Ding, Hua Wang, Heng Huang, 2012, ECCV.

Integrated KL (K-means - Laplacian) Clustering: A New Clustering Approach by Combining Attribute Data and Pairwise Relations

Fei Wang, Chris H. Q. Ding, Tao Li, 2009, SDM.

A Parallel Implementation of the TOUGH2 Software Package for Large Scale Multiphase Fluid and Heat Flow Simulations

Erik Elmroth, Chris H. Q. Ding, Karsten Pruess, 1999, SC.

Bridging Domains with Words: Opinion Analysis with Matrix Tri-factorizations

Chris H. Q. Ding, Tao Li, Yi Zhang, 2010, SDM.

Efficient and Robust Feature Selection via Joint ℓ2, 1-Norms Minimization

Feiping Nie, Chris H. Q. Ding, Heng Huang, 2010, NIPS.

Maximum Consistency Preferential Random Walks

Chris H. Q. Ding, Deguang Kong, C. Ding, 2012, ECML/PKDD.

Robust Non-Negative Dictionary Learning

Chris H. Q. Ding, Bin Luo, Deguang Kong, 2014, AAAI.

A discriminative multi-class feature selection method via weighted l2, 1-norm and Extended Elastic Net

Ying Zhang, Chris H. Q. Ding, Bin Luo, 2018, Neurocomputing.

Stable feature selection via dense feature groups

Chris H. Q. Ding, Lei Yu, Steven Loscalzo, 2008, KDD.

Transitive closure and metric inequality of weighted graphs: detecting protein interaction modules using cliques

Hui Xiong, Chris H. Q. Ding, Hanchuan Peng, 2006, Int. J. Data Min. Bioinform..

eQTL epistasis: detecting epistatic effects and inferring hierarchical relationships of genes in biological pathways

Chris H. Q. Ding, Jean Gao, Chunling Zhang, 2015, Bioinform..

Robust Manifold Nonnegative Matrix Factorization

Feiping Nie, Chris H. Q. Ding, Heng Huang, 2014, ACM Trans. Knowl. Discov. Data.

A Two-Stage Gene Selection Algorithm by Combining ReliefF and mRMR

Chris H. Q. Ding, Tao Li, Yi Zhang, 2007, BIBE.

Comparative mapping of sequence-based and structure-based protein domains

Chris H. Q. Ding, Ya Zhang, Stephen R. Holbrook, 2004, BMC Bioinformatics.

Multi-label ReliefF and F-statistic feature selections for image annotation

Chris H. Q. Ding, Heng Huang, Haifeng Zhao, 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

Nonnegative Matrix Factorization and Probabilistic Latent Semantic Indexing: Equivalence Chi-Square Statistic, and a Hybrid Method

Chris H. Q. Ding, Wei Peng, Tao Li, 2006, AAAI.

R1-PCA: rotational invariant L1-norm principal component analysis for robust subspace factorization

Chris H. Q. Ding, Hongyuan Zha, Xiaofeng He, 2006, ICML.

Chris H. Q. Ding, Bo Jiang, Bin Luo, 2014, ECML/PKDD.

Improved MinMax Cut Graph Clustering with Nonnegative Relaxation

Feiping Nie, Chris H. Q. Ding, Heng Huang, 2010, ECML/PKDD.

Solving Consensus and Semi-supervised Clustering Problems Using Nonnegative Matrix Factorization

Chris H. Q. Ding, Michael I. Jordan, Tao Li, 2007, Seventh IEEE International Conference on Data Mining (ICDM 2007).

Development Of A Modular Performance-Portable Climate System Model

Chris H. Q. Ding, David P. Williamson, Ian Foster, 2001 .

Similarity Learning of Manifold Data

Bin Luo, Chris H. Q. Ding, Si-Bao Chen, 2015, IEEE Transactions on Cybernetics.

Multiple Images Recovery Using a Single Affine Transformation pdf

Chris H. Q. Ding, Bo Jiang, Bin Luo, 2017, ArXiv.

Unsupervised Learning: Self-aggregation in Scaled Principal Component Space

Chris H. Q. Ding, Hongyuan Zha, Xiaofeng He, 2002, PKDD.

Multi-label Linear Discriminant Analysis

Chris H. Q. Ding, Hua Wang, Heng Huang, 2010, ECCV.

A Local Sparse Model for Matching Problem

Chris H. Q. Ding, Bo Jiang, Jin Tang, 2015, AAAI.

Discriminative high order SVD: Adaptive tensor subspace selection for image classification, clustering, and retrieval

Chris H. Q. Ding, Heng Huang, Dijun Luo, 2011, 2011 International Conference on Computer Vision.

Link Analysis: Hubs and Authorities on the World Wide Web

Chris H. Q. Ding, Hongyuan Zha, Xiaofeng He, 2004, SIAM Rev..

K-Subspace Clustering

Chris H. Q. Ding, Tao Li, Dingding Wang, 2009, ECML/PKDD.

An Iterative Locally Linear Embedding Algorithm

Feiping Nie, Chris H. Q. Ding, Heng Huang, 2012, ICML.

Unsupervised and semi-supervised learning via ℓ1-norm graph

Feiping Nie, Chris H. Q. Ding, Hua Wang, 2011, 2011 International Conference on Computer Vision.

A general purpose sparse matrix parallel solvers package

Chris H. Q. Ding, Robert D. Ferraro, C. Ding, 1995, Proceedings of 9th International Parallel Processing Symposium.

Regularization graph convolutional networks with data augmentation

Chris H. Q. Ding, Sibao Chen, Xin Wang, 2021, Neurocomputing.

Nonnegative Orthogonal Graph Matching

Chris H. Q. Ding, Jin Tang, Bo Jiang, 2017, AAAI.