- CONVEX AND SEMI-NONNEGATIVE MATRIX FACTORIZATIONS: DING, LI AND JORDAN 1 Convex and Semi-Nonnegative Matrix
- Nonnegative Matrix Factorization for Combinatorial Optimization: Spectral Clustering, Graph Matching, and Clique Finding
- Linearized Cluster Assignment via Spectral Ordering Chris Ding chqding@lbl.gov
- A spectral method to separate disconnected and nearlydisconnected Web graph components
- Proc. of PKDD2002, pp.112124. 1 Unsupervised Learning: Selfaggregation in Scaled
- Cluster Aggregate Inequality and MultiLevel Hierarchical Clustering
- Structure Search and Stability Enhancement of Bayesian Networks Hanchuan Peng and Chris Ding
- A MinMaxCut Spectral Method for Data Clustering and Graph Partitioning
- Simultaneous Tensor Subspace Selection and Clustering: The Equivalence of High Order SVD and K-Means
- PageRank, HITS and a Unified Framework for Link Analysis Chris Ding # , Xiaofeng He # , Parry Husbands # , Hongyuan Zha + , Horst Simon #
- Automatic Topic Identi cation Using Webpage Clustering Xiaofeng He a;b , Chris H.Q. Ding b , Hongyuan Zha a , Horst D. Simon b
- Document Retrieval and Clustering: from Principal Component Analysis to Self-aggregation Networks
- Computational Statistics and Data Analysis 52 (2008) 39133927 www.elsevier.com/locate/csda
- Positive Sample Only Learning (PSOL) for Predicting RNA Genes in E. coli Richard F. Meraz1
- A Probabilistic Model for Latent Semantic Indexing Chris H.Q. Ding
- Linearized Cluster Assignment via Spectral Ordering Chris Ding chqding@lbl.gov
- This paper is published in Bioinformatics, v.17, no.4, pp.349-358, April 2001. 1 Multi-class Protein Fold Recognition Using Support Vector
- Minimum Redundancy Feature Selection from Microarray Gene Expression Data
- A Unified Representation of Multi-Protein Complex Data Chris Ding, Xiaofeng He, Richard F. Meraz, Stephen R. Holbrook
- Convex and Semi-Nonnegative Matrix Factorizations Lawrence Berkeley National Laboratory
- Tensor Reduction Error Analysis Applications to Video Compression and Classification
- On the Equivalence of Nonnegative Matrix Factorization and Spectral Clustering
- A Min-max Cut Algorithm for Graph Partitioning and Data Clustering Chris H.Q. Ding a , Xiaofeng He a;b , Hongyuan Zha b , Ming Gu c , Horst D. Simon a
- Proc. of PKDD2002, pp.112-124. 1 Unsupervised Learning: Self-aggregation in Scaled
- Adaptive Dimension Reduction Using Discriminant Analysis and K-means Chris Ding CHQDING@LBL.GOV
- LINK ANALYSIS: HUBS AND AUTHORITIES ON THE WORLD CHRIS H.Q. DING, HONGYUAN ZHA , XIAOFENG HE , PARRY HUSBANDS , AND
- Posterior Probabilistic Clustering using NMF CSE Department
- Cluster merging and splitting in hierarchical clustering algorithms Chris Ding and Xiaofeng He
- Data Clustering: Principal Components, Hopfield and SelfAggregation Networks Chris H.Q. Ding
- Ding&Ferraro 7 10 Conclusions
- (SIGIR'99, pp.59-65. Updated version, as presented in the conference.) 1 A Similarity-based Probability Model for Latent Semantic Indexing
- KNearestNeighbor Consistency in Data Clustering: Incorporating Local Information into Global Optimization
- Two-Dimensional Singular Value Decomposition (2DSVD) for 2D Maps and Images
- (IEEE Transactions on Parallel and Distributed Systems, Vol. 12, No.3, March 2001, pp.306-315)1 An Optimal Index Reshu e Algorithm for
- Adaptive dimension reduction for clustering high dimensional data Chris Ding a , Xiaofeng He a , Hongyuan Zha b and Horst D. Simon a
- K-means Clustering via Principal Component Analysis Chris Ding chqding@lbl.gov
- A Portable 3D FFT Package for DistributedMemory Parallel Architectures \Lambda
- Knowledge Transformation from Word Space to Document School of Computer Science
- R1-PCA: Rotational Invariant L1-norm Principal Component Analysis for Robust Subspace Factorization
- Symmetric Two Dimensional Linear Discriminant Analysis (2DLDA) Dijun Luo, Chris Ding, Heng Huang
- Integrated KL (K-means -Laplacian) Clustering: A New Clustering Approach by Combining Attribute Data and Pairwise Relations
- Robust Tensor Factorization Using R1 Norm Computer Science and Engineering
- This Provisional PDF corresponds to the article as it appeared upon acceptance. Copyedited and fully formatted PDF and full text (HTML) versions will be made available soon.
- The Relationships Among Various Nonnegative Matrix Factorization Methods for Clustering
- Binary Matrix Factorization with Applications Zhongyuan Zhang
- Transitive Closure and Metric Inequality of Weighted Graphs Detecting Protein Interaction Modules Using Cliques
- Nonnegative Matrix Factorization and Probabilistic Latent Semantic Indexing: Equivalence, Chi-square Statistic, and a Hybrid Method
- Orthogonal Nonnegative Matrix Tri-Factorizations for Lawrence Berkeley National
- to a response. The computational complex-ity is that of Random Forest, O( N log
- Feature Selection Based on Mutual Information: Criteria of Max-Dependency, Max-Relevance,
- Journal of Bioinformatics and Computational Biology Vol. 3, No. 2 (2005) 185205
- Spectral Relaxation for K-means Hongyuan Zha & Xiaofeng He
- c5 c6c4c3c2c1 r3r2 r4 r5 r6 r7
- Dynamic Cluster Formation using Level Set Methods Andy M. Yip
