Inderjit S. Dhillon

Kai-Yang Chiang, Cho-Jui Hsieh, Nagarajan Natarajan, Ambuj Tewari, Inderjit S. Dhillon: Prediction and Clustering in Signed Networks: A Local to Global Perspective. CoRR abs/1302.5145 (2013)

Prateek Jain, Brian Kulis, Jason V. Davis, Inderjit S. Dhillon: Metric and Kernel Learning Using a Linear Transformation. Journal of Machine Learning Research 13: 519-547 (2012)

Mátyás A. Sustik, Inderjit S. Dhillon: On a Zero-Finding Problem Involving the Matrix Exponential. SIAM J. Matrix Analysis Applications 33(4): 1237-1249 (2012)

Donghyuk Shin, Si Si, Inderjit S. Dhillon: Multi-scale link prediction. CIKM 2012: 215-224

Kai-Yang Chiang, Joyce Jiyoung Whang, Inderjit S. Dhillon: Scalable clustering of signed networks using balance normalized cut. CIKM 2012: 615-624

Joyce Jiyoung Whang, Xin Sui, Inderjit S. Dhillon: Scalable and Memory-Efficient Clustering of Large-Scale Social Networks. ICDM 2012: 705-714

Hsiang-Fu Yu, Cho-Jui Hsieh, Si Si, Inderjit S. Dhillon: Scalable Coordinate Descent Approaches to Parallel Matrix Factorization for Recommender Systems. ICDM 2012: 765-774

Cho-Jui Hsieh, Kai-Yang Chiang, Inderjit S. Dhillon: Low rank modeling of signed networks. KDD 2012: 507-515

Xin Sui, Tsung-Hsien Lee, Joyce Jiyoung Whang, Berkant Savas, Saral Jain, Keshav Pingali, Inderjit S. Dhillon: Parallel Clustered Low-Rank Approximation of Graphs and Its Application to Link Prediction. LCPC 2012: 76-95

Cho-Jui Hsieh, Inderjit S. Dhillon, Pradeep D. Ravikumar, Arindam Banerjee: A Divide-and-Conquer Method for Sparse Inverse Covariance Estimation. NIPS 2012: 2339-2347

Han Hee Song, Berkant Savas, Tae Won Cho, Vacha Dave, Zhengdong Lu, Inderjit S. Dhillon, Yin Zhang, Lili Qiu: Clustered embedding of massive social networks. SIGMETRICS 2012: 331-342

Donghyuk Shin, Si Si, Inderjit S. Dhillon: Multi-Scale Link Prediction. CoRR abs/1206.1891 (2012)

Alexandre d'Aspremont, Francis R. Bach, Inderjit S. Dhillon, Bin Yu: Preface. Math. Program. 127(1): 1-2 (2011)

Vishvas Vasuki, Nagarajan Natarajan, Zhengdong Lu, Berkant Savas, Inderjit S. Dhillon: Scalable Affiliation Recommendation using Auxiliary Networks. ACM TIST 3(1): 3 (2011)

Kai-Yang Chiang, Nagarajan Natarajan, Ambuj Tewari, Inderjit S. Dhillon: Exploiting longer cycles for link prediction in signed networks. CIKM 2011: 1157-1162

Cho-Jui Hsieh, Inderjit S. Dhillon: Fast coordinate descent methods with variable selection for non-negative matrix factorization. KDD 2011: 1064-1072

Ambuj Tewari, Pradeep D. Ravikumar, Inderjit S. Dhillon: Greedy Algorithms for Structurally Constrained High Dimensional Problems. NIPS 2011: 882-890

Prateek Jain, Ambuj Tewari, Inderjit S. Dhillon: Orthogonal Matching Pursuit with Replacement. NIPS 2011: 1215-1223

Inderjit S. Dhillon, Pradeep D. Ravikumar, Ambuj Tewari: Nearest Neighbor based Greedy Coordinate Descent. NIPS 2011: 2160-2168

Cho-Jui Hsieh, Mátyás A. Sustik, Inderjit S. Dhillon, Pradeep D. Ravikumar: Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation. NIPS 2011: 2330-2338

Berkant Savas, Inderjit S. Dhillon: Clustered low rank approximation of graphs in information science applications. SDM 2011: 164-175

Prateek Jain, Ambuj Tewari, Inderjit S. Dhillon: Orthogonal Matching Pursuit with Replacement. CoRR abs/1106.2774 (2011)

Dongmin Kim, Suvrit Sra, Inderjit S. Dhillon: Tackling Box-Constrained Optimization via a New Projected Quasi-Newton Approach. SIAM J. Scientific Computing 32(6): 3548-3563 (2010)

Zhengdong Lu, Berkant Savas, Wei Tang, Inderjit S. Dhillon: Supervised Link Prediction Using Multiple Sources. ICDM 2010: 923-928

Dongmin Kim, Suvrit Sra, Inderjit S. Dhillon: A scalable trust-region algorithm with application to mixed-norm regression. ICML 2010: 519-526

Prateek Jain, Raghu Meka, Inderjit S. Dhillon: Guaranteed Rank Minimization via Singular Value Projection. NIPS 2010: 937-945

Prateek Jain, Brian Kulis, Inderjit S. Dhillon: Inductive Regularized Learning of Kernel Functions. NIPS 2010: 946-954

Vishvas Vasuki, Nagarajan Natarajan, Zhengdong Lu, Inderjit S. Dhillon: Affiliation recommendation using auxiliary networks. RecSys 2010: 103-110

Brian Kulis, Suvrit Sra, Inderjit S. Dhillon: Convex Perturbations for Scalable Semidefinite Programming. Journal of Machine Learning Research - Proceedings Track 5: 296-303 (2009)

Brian Kulis, Mátyás A. Sustik, Inderjit S. Dhillon: Low-Rank Kernel Learning with Bregman Matrix Divergences. Journal of Machine Learning Research 10: 341-376 (2009)

Brian Kulis, Sugato Basu, Inderjit S. Dhillon, Raymond J. Mooney: Semi-supervised graph clustering: a kernel approach. Machine Learning 74(1): 1-22 (2009)

Wei Tang, Zhengdong Lu, Inderjit S. Dhillon: Clustering with Multiple Graphs. ICDM 2009: 1016-1021

Meghana Deodhar, Gunjan Gupta, Joydeep Ghosh, Hyuk Cho, Inderjit S. Dhillon: A scalable framework for discovering coherent co-clusters in noisy data. ICML 2009: 31

Zhengdong Lu, Prateek Jain, Inderjit S. Dhillon: Geometry-aware metric learning. ICML 2009: 85

Raghu Meka, Prateek Jain, Inderjit S. Dhillon: Matrix Completion from Power-Law Distributed Samples. NIPS 2009: 1258-1266

Zhengdong Lu, Deepak Agarwal, Inderjit S. Dhillon: A spatio-temporal approach to collaborative filtering. RecSys 2009: 13-20

Pavel Berkhin, Inderjit S. Dhillon: Knowledge Discovery: Clustering. Encyclopedia of Complexity and Systems Science 2009: 5051-5064

Raghu Meka, Prateek Jain, Inderjit S. Dhillon: Guaranteed Rank Minimization via Singular Value Projection. CoRR abs/0909.5457 (2009)

Inderjit S. Dhillon, Robert W. Heath Jr., Thomas Strohmer, Joel A. Tropp: Constructing Packings in Grassmannian Manifolds via Alternating Projection. Experimental Mathematics 17(1): 9-35 (2008)

Dongmin Kim, Suvrit Sra, Inderjit S. Dhillon: Fast Projection-Based Methods for the Least Squares Nonnegative Matrix Approximation Problem. Statistical Analysis and Data Mining 1(1): 38-51 (2008)

Prateek Jain, Raghu Meka, Inderjit S. Dhillon: Simultaneous Unsupervised Learning of Disparate Clusterings. Statistical Analysis and Data Mining 1(3): 195-210 (2008)

Justin Brickell, Inderjit S. Dhillon, Suvrit Sra, Joel A. Tropp: The Metric Nearness Problem. SIAM J. Matrix Analysis Applications 30(1): 375-396 (2008)

Hyuk Cho, Inderjit S. Dhillon: Coclustering of Human Cancer Microarrays Using Minimum Sum-Squared Residue Coclustering. IEEE/ACM Trans. Comput. Biology Bioinform. 5(3): 385-400 (2008)

Meghana Deodhar, Joydeep Ghosh, Gunjan Gupta, Hyuk Cho, Inderjit S. Dhillon: Hunting for Coherent Co-clusters in High Dimensional and Noisy Datasets. ICDM Workshops 2008: 654-663

Raghu Meka, Prateek Jain, Constantine Caramanis, Inderjit S. Dhillon: Rank minimization via online learning. ICML 2008: 656-663

Jason V. Davis, Inderjit S. Dhillon: Structured metric learning for high dimensional problems. KDD 2008: 195-203

Prateek Jain, Brian Kulis, Inderjit S. Dhillon, Kristen Grauman: Online Metric Learning and Fast Similarity Search. NIPS 2008: 761-768

Prateek Jain, Raghu Meka, Inderjit S. Dhillon: Simultaneous Unsupervised Learning of Disparate Clusterings. SDM 2008: 858-869

Arindam Banerjee, Inderjit S. Dhillon, Joydeep Ghosh, Srujana Merugu, Dharmendra S. Modha: A Generalized Maximum Entropy Approach to Bregman Co-clustering and Matrix Approximation. Journal of Machine Learning Research 8: 1919-1986 (2007)

Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis: Weighted Graph Cuts without Eigenvectors A Multilevel Approach. IEEE Trans. Pattern Anal. Mach. Intell. 29(11): 1944-1957 (2007)

Inderjit S. Dhillon, Joel A. Tropp: Matrix Nearness Problems with Bregman Divergences. SIAM J. Matrix Analysis Applications 29(4): 1120-1146 (2007)

Jason V. Davis, Brian Kulis, Prateek Jain, Suvrit Sra, Inderjit S. Dhillon: Information-theoretic metric learning. ICML 2007: 209-216

Dongmin Kim, Suvrit Sra, Inderjit S. Dhillon: Fast Newton-type Methods for the Least Squares Nonnegative Matrix Approximation Problem. SDM 2007

Inderjit S. Dhillon, Beresford N. Parlett, Christof Vömel: The design and implementation of the MRRR algorithm. ACM Trans. Math. Softw. 32(4): 533-560 (2006)

Brian Kulis, Mátyás A. Sustik, Inderjit S. Dhillon: Learning low-rank kernel matrices. ICML 2006: 505-512

Justin Brickell, Inderjit S. Dhillon, Dharmendra S. Modha: Adaptive Website Design Using Caching Algorithms. WEBKDD 2006: 1-20

Jason V. Davis, Inderjit S. Dhillon: Estimating the global pagerank of web communities. KDD 2006: 116-125

Jason V. Davis, Inderjit S. Dhillon: Differential Entropic Clustering of Multivariate Gaussians. NIPS 2006: 337-344

Arindam Banerjee, Inderjit S. Dhillon, Joydeep Ghosh, Suvrit Sra: Clustering on the Unit Hypersphere using von Mises-Fisher Distributions. Journal of Machine Learning Research 6: 1345-1382 (2005)

Arindam Banerjee, Srujana Merugu, Inderjit S. Dhillon, Joydeep Ghosh: Clustering with Bregman Divergences. Journal of Machine Learning Research 6: 1705-1749 (2005)

Inderjit S. Dhillon, Robert W. Heath Jr., Mátyás A. Sustik, Joel A. Tropp: Generalized Finite Algorithms for Constructing Hermitian Matrices with Prescribed Diagonal and Spectrum. SIAM J. Matrix Analysis Applications 27(1): 61-71 (2005)

Paolo Bientinesi, Inderjit S. Dhillon, Robert A. van de Geijn: A Parallel Eigensolver for Dense Symmetric Matrices Based on Multiple Relatively Robust Representations. SIAM J. Scientific Computing 27(1): 43-66 (2005)

Inderjit S. Dhillon, Beresford N. Parlett, Christof Vömel: Glued Matrices and the MRRR Algorithm. SIAM J. Scientific Computing 27(2): 496-510 (2005)

Joel A. Tropp, Inderjit S. Dhillon, Robert W. Heath Jr., Thomas Strohmer: Designing structured tight frames via an alternating projection method. IEEE Transactions on Information Theory 51(1): 188-209 (2005)

Brian Kulis, Sugato Basu, Inderjit S. Dhillon, Raymond J. Mooney: Semi-supervised graph clustering: a kernel approach. ICML 2005: 457-464

Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis: A fast kernel-based multilevel algorithm for graph clustering. KDD 2005: 629-634

Inderjit S. Dhillon, Suvrit Sra: Generalized Nonnegative Matrix Approximations with Bregman Divergences. NIPS 2005

Joel A. Tropp, Inderjit S. Dhillon, Robert W. Heath Jr.: Finite-Step Algorithms for Constructing Optimal CDMA Signature Sequences. IEEE Transactions on Information Theory 50(11): 2916-2921 (2004)

Arindam Banerjee, Inderjit S. Dhillon, Joydeep Ghosh, Srujana Merugu: An information theoretic analysis of maximum likelihood mixture estimation for exponential families. ICML 2004

Arindam Banerjee, Inderjit S. Dhillon, Joydeep Ghosh, Srujana Merugu, Dharmendra S. Modha: A generalized maximum entropy approach to bregman co-clustering and matrix approximation. KDD 2004: 509-514

Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis: Kernel k-means: spectral clustering and normalized cuts. KDD 2004: 551-556

Inderjit S. Dhillon, Suvrit Sra, Joel A. Tropp: Triangle Fixing Algorithms for the Metric Nearness Problem. NIPS 2004

Arindam Banerjee, Srujana Merugu, Inderjit S. Dhillon, Joydeep Ghosh: Clustering with Bregman Divergences. SDM 2004

Hyuk Cho, Inderjit S. Dhillon, Yuqiang Guan, Suvrit Sra: Minimum Sum-Squared Residue Co-Clustering of Gene Expression Data. SDM 2004

Inderjit S. Dhillon, Edward M. Marcotte, Usman Roshan: Diametrical clustering for identifying anti-correlated gene clusters. Bioinformatics 19(13): 1612-1619 (2003)

Inderjit S. Dhillon, Subramanyam Mallela, Rahul Kumar: A Divisive Information-Theoretic Feature Clustering Algorithm for Text Classification. Journal of Machine Learning Research 3: 1265-1287 (2003)

Inderjit S. Dhillon, Beresford N. Parlett: Orthogonal Eigenvectors and Relative Gaps. SIAM J. Matrix Analysis Applications 25(3): 858-899 (2003)

Inderjit S. Dhillon, Yuqiang Guan: Information Theoretic Clustering of Sparse Co-Occurrence Data. ICDM 2003: 517-520

Arindam Banerjee, Inderjit S. Dhillon, Joydeep Ghosh, Suvrit Sra: Generative model-based clustering of directional data. KDD 2003: 19-28

Inderjit S. Dhillon, Subramanyam Mallela, Dharmendra S. Modha: Information-theoretic co-clustering. KDD 2003: 89-98

Inderjit S. Dhillon, Dharmendra S. Modha, W. Scott Spangler: Class visualization of high-dimensional data with applications. Computational Statistics & Data Analysis 41(1): 59-90 (2002)

Inderjit S. Dhillon, Yuqiang Guan, Jacob Kogan: Iterative Clustering of High Dimensional Text Data Augmented by Local Search. ICDM 2002: 131-138

Inderjit S. Dhillon, Subramanyam Mallela, Rahul Kumar: Enhanced word clustering for hierarchical text classification. KDD 2002: 191-200

Inderjit S. Dhillon, Dharmendra S. Modha: Concept Decompositions for Large Sparse Text Data Using Clustering. Machine Learning 42(1/2): 143-175 (2001)

Inderjit S. Dhillon: Co-clustering documents and words using bipartite spectral graph partitioning. KDD 2001: 269-274

Inderjit S. Dhillon, Dharmendra S. Modha: A Data-Clustering Algorithm on Distributed Memory Multiprocessors. Large-Scale Parallel Data Mining 1999: 245-260

L. Susan Blackford, Andrew J. Cleary, Antoine Petitet, R. Clinton Whaley, James Demmel, Inderjit S. Dhillon, H. Ren, Ken Stanley, Jack Dongarra, Sven Hammarling: Practical Experience in the Numerical Dangers of Heterogeneous Computing. ACM Trans. Math. Softw. 23(2): 133-147 (1997)

L. Susan Blackford, Jaeyoung Choi, Andrew J. Cleary, Eduardo F. D'Azevedo, James Demmel, Inderjit S. Dhillon, Jack Dongarra, Sven Hammarling, Greg Henry, Antoine Petitet, Ken Stanley, David W. Walker, R. Clinton Whaley: ScaLAPACK: A Linear Algebra Library for Message-Passing Computers. PPSC 1997

Inderjit S. Dhillon, George Fann, Beresford N. Parlett: Application of a New Algorithm for the Symmetric Eigenproblem to Computational Quantum Chemistry. PPSC 1997

Andrew J. Cleary, James Demmel, Inderjit S. Dhillon, Jack Dongarra, Sven Hammarling, Antoine Petitet, H. Ren, Ken Stanley, R. Clinton Whaley: Practical Experience in the Dangers of Heterogeneous Computing. PARA 1996: 57-64

L. Susan Blackford, Jaeyoung Choi, Andrew J. Cleary, James Demmel, Inderjit S. Dhillon, Jack Dongarra, Sven Hammarling, Greg Henry, Antoine Petitet, Ken Stanley, David W. Walker, R. Clinton Whaley: ScaLAPACK: A Portable Linear Algebra Library for Distributed Memory Computers - Design Issues and Performance. SC 1996: 5

Jaeyoung Choi, James Demmel, Inderjit S. Dhillon, Jack Dongarra, Susan Ostrouchov, Antoine Petitet, Ken Stanley, David W. Walker, R. Clinton Whaley: ScaLAPACK: A Portable Linear Algebra Library for Distributed Memory Computers - Design Issues and Performance. PARA 1995: 95-106