(Organized by TOPIC)
(Go to complete list by TYPE or by YEAR)
- Data Mining & Machine Learning
- Bioinformatics
- Computational Linear Algebra
Learning with Bregman Divergences
- Hunting for Coherent Co-clusters in High Dimensional and Noisy Datasets
M. Deodhar, H. Cho, G. Gupta, J. Ghosh, and I. S. Dhillon
To appear in IEEE International Conference on Data Mining (ICDM) (Workshop on Foundations on Data Mining (FDM-2008)), December 2008.
Download: [not available]
- Low-Rank Kernel Learning with Bregman Matrix Divergences
B. Kulis, M. Sustik, and I. S. Dhillon
To appear in Journal of Machine Learning Research (JMLR), 2008.
Download: [pdf]
- Structured Metric Learning for High-Dimensional Problems
J. Davis and I. S. Dhillon
Proceedings of the Fourteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), August 2008.
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- Matrix Nearness Problems with Bregman Divergences
I. S. Dhillon and J. A. Tropp
SIAM Journal on Matrix Analysis and Applications, vol. 29:4, pages 1120-1146, November 2007.
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- A Generalized Maximum Entropy Approach to Bregman Co-clustering and Matrix Approximations
A. Banerjee, I. S. Dhillon, J. Ghosh, S. Merugu, and D. S. Modha
Journal of Machine Learning Research (JMLR), vol. 8, pages 1919-1986, August 2007.
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- Information-Theoretic Metric Learning
J. V. Davis, B. Kulis, P. Jain, S. Sra, and I. S. Dhillon
Proceedings of the the Twenty-Fourth International Conference on Machine Learning (ICML), pages 209-216, June 2007.
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- Online Linear Regression using Burg Entropy
P. Jain, B. Kulis, and I. S. Dhillon
UTCS Technical Report #TR-07-08, February 2007. [Abstract & Download])- Differential Entropic Clustering of Multivariate Gaussians
J. Davis and I. S. Dhillon
Nineteenth Annual Conference on Neural Information Processing Systems (NIPS), pages 337-344, December 2006.
Download: [pdf]- Learning Low-Rank Kernel Matrices
B. Kulis, M. A. Sustik, and I. S. Dhillon
Proceedings of the Twenty-third International Conference on Machine Learning (ICML), pages 505-512, July 2006.
Download: [pdf]- Clustering with Bregman Divergences
A. Banerjee, S. Merugu, I. S. Dhillon, and J. Ghosh
Journal of Machine Learning Research (JMLR), vol. 6, pages 1705-1749, October 2005.
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- Clustering with Entropy-like k-means Algorithms
M. Teboulle, P. Berkhin, I. S. Dhillon, Y. Guan, and J. Kogan
Invited book chapter in Grouping Multidimensional Data - Recent Advances in Clustering, Springer-Verlag, pages 127-160, 2005.
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- A Generalized Maximum Entropy Approach to Bregman Co-colustering and Matrix Approximations
A. Banerjee, I. S. Dhillon, J. Ghosh, S. Merugu, and D. S. Modha
Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pages 509-514, August 2004.
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(A longer version appears as UTCS Technical Report #TR-04-24, September 2004. [Abstract & Download])
- An Information Theoretic Analysis of Maximum Likelihood Mixture Estimation for Exponential Families
A. Banerjee, I. S. Dhillon, J. Ghosh, and S. Merugu
Proceedings of the Twenty-First International Conference on Machine Learning (ICML), pages 57-64, July 2004
Download: [pdf]- Clustering with Bregman Divergences
A. Banerjee, S. Merugu, I. S. Dhillon, and J. Ghosh
Proceedings of the Fourth SIAM International Conference on Data Mining, pages 234-245, April 2004
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Information Theoretic Clustering
- Information-Theoretic Co-clustering
I. S. Dhillon, S. Mallela, and D. S. Modha
Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pages 89-98, August 2003.
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(Also appears as UTCS Technical Report #TR-03-12, April 2003. [Abstract & Download])- A Divisive Information-Theoretic Feature Clustering Algorithm for Text Classification
I. S. Dhillon, S. Mallela, and R. Kumar
Journal of Machine Learning Research (JMLR), vol. 3, pages 1265-1287, March 2003.
Download: [pdf]- Information Theoretic Clustering of Sparse Co-Occurrence Data
I. S. Dhillon and Y. Guan
Proceedings of the Third IEEE International Conference on Data Mining, pages 517-520, November 2003
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(A longer version appears as UTCS Technical Report #TR-03-39, September 2003. [Abstract & Download])
(Also appears as "Clustering Large and Sparse Co-Occurrence Data", Workshop on Clustering High-Dimensional Data and its Applications at the Third SIAM International Conference on Data Mining, May 2003. Download: [pdf])- Enhanced Word Clustering for Hierarchical Text Classification
I. S. Dhillon, S. Mallela, and R. Kumar
Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), July 2002.
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(Also appears as UTCS Technical Report #TR-02-17, March 2002. [Abstract & Download])Back to Top
Nonnegative Matrix Approximation
- Fast Projection-Based Methods for the Least Squares Nonnegative Matrix Approximation Problem
D. Kim, S. Sra, and I. S. Dhillon
Statistical Analysis and Data Mining, vol. 1:1, pages 38-51, February 2008.
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- Fast Newton-type Methods for the Least Squares Nonnegative Matrix Approximation Problem
D. Kim, S. Sra, and I. S. Dhillon
Proceedings of the Sixth SIAM International Conference on Data Mining, pages 343-354, April 2007.
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- Nonnegative Matrix Approximation: Algorithms and Applications
S. Sra and I. S. Dhillon
UTCS Technical Report #TR-06-27, June 2006. [Abstract & Download])- Generalized Nonnegative Matrix Approximations with Bregman Divergences
I. S. Dhillon and S. Sra
Proceedings of the Neural Information Processing Systems Conference (NIPS), pages 283-290, Vancouver Canada, December 2005.
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(Also appears as UTCS Technical Report #TR-05-31, June 1, 2005. [Abstract & Download])Back to Top
High Dimensional Clustering
- Clustering on the Unit Hypersphere using von Mises-Fisher Distributions
A. Banerjee, I. S. Dhillon, J. Ghosh, and S. Sra
Journal of Machine Learning Research (JMLR), vol. 6, pages 1345-1382, September 2005.
Download: [pdf]- Generative Model-based Clustering of Directional Data
A. Banerjee, I. S. Dhillon, J. Ghosh, and S. Sra
Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pages 19-28, August 2003.
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- Expectation Maximization for Clustering on Hyperspheres
A. Banerjee, I. S. Dhillon, J. Ghosh, and S. Sra
UTCS Technical Report #TR-03-07, February 2003. [Abstract & Download]- Modeling data using Directional Distributions
I. S. Dhillon and S. Sra
UTCS Technical Report #TR-03-06, January 2003. [Abstract & Download]- Feature Selection and Document Clustering
I. S. Dhillon, J. Kogan, and M. Nicholas
Book chapter in A Comprehensive Survey of Text Mining, Springer-Verlag, pages 73-100, 2003.
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- Iterative Clustering of High Dimensional Text Data Augmented by Local Search
I. S. Dhillon, Y. Guan, and J. Kogan
Proceedings of the Second IEEE International Conference on Data Mining, pages 131-138, Maebishi, Japan, December 2002.
Download: [pdf]- Refining Clusters in High-dimensional Text Data
I. S. Dhillon, Y. Guan, and J. Kogan
2nd SIAM International Conference on Data Mining (Workshop on Clustering High-Dimensional Data and its Applications), April 2002.
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(Also appears as UTCS Technical Report #TR-02-03, January 2002. [Abstract & Download])- Concept Decompositions for Large Sparse Text Data using Clustering
I. S. Dhillon and D. S. Modha
Machine Learning, vol. 42:1, pages 143-175, January 2001.
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(An earlier version appears as IBM Research Report RJ 10147, July 8, 1999.)- Efficient Clustering of Very Large Document Collections
I. S. Dhillon, Y. Guan, and J. Fan
Invited book chapter in Data Mining for Scientific and Engineering Applications, Kluwer Academic Publishers, pages 357-381, 2001.
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Spectral Clustering
- Semi-Supervised Graph-Based Clustering: A Kernel Approach
B. Kulis, S. Basu, I. S. Dhillon, and R. J. Mooney
To appear in Machine Learning, 2008.
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- Weighted Graph Cuts without Eigenvectors: A Multilevel Approach
I. S. Dhillon, Y. Guan, and B. Kulis
IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol. 29:11, pages 1944-1957, November 2007.
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- A Fast Kernel-based Multilevel Algorithm for Graph Clustering
I. S. Dhillon, Y. Guan, and B. Kulis
Proceedings of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pages 629-634, August 2005.
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- Semi-supervised Graph Clustering: A Kernel Approach
B. Kulis, S. Basu, I. S. Dhillon, and R. J. Mooney
Proceedings of the Twenty-second International Conference on Machine Learning (ICML), pages 457-464, July 2005.
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- A Unified View of Kernel k-means, Spectral Clustering and Graph Partitioning
I. S. Dhillon, Y. Guan, and B. Kulis
Submitted for publication, January 2005.
(Also appears as UTCS Technical Report #TR-04-25, June 30, 2004. [Abstract & Download])- Kernel k-means, Spectral Clustering and Normalized Cuts
I. S. Dhillon, Y. Guan, and B. Kulis
Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pages 551-556, August 2004.
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(Also appears as UTCS Technical Report #TR-04-25, June 30, 2004. [Abstract & Download])- Co-clustering Documents and Words Using Bipartite Spectral Graph Partitioning
I. S. Dhillon
Proceedings of the Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), August 26-29, 2001, San Francisco, California, USA
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(Also a longer version appears as UTCS Technical Report #TR-01-05, March 2001. [Abstract & Download])Back to Top
Disparate Clusterings
- Unsupervised Learning of Disparate Clusterings
P. Jain, R. Meka, and I. S. Dhillon
To appear in Statistical Analysis and Data Mining, 2008.
Download: [not available]
- Simultaneous Unsupervised Learning of Disparate Clusterings
P. Jain, R. Meka, and I. S. Dhillon
Proceedings of the Seventh SIAM International Converence on Data Mining, pages 858-869, April 2008.
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Minimum Rank Problems
- Rank Minimization via Online Learning
P. Jain, R. Meka, C. Caramanis, and I. S. Dhillon
Proceedings of the Twenty-Fifth International Conference on Machine Learning (ICML), July 2008.
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Data Visualization
- Class Visualization of High-Dimensional Data with Applications
I. S. Dhillon, D. S. Modha, and W. S. Spangler
Computational Statistics & Data Analysis (Special issue on Matrix Computations & Statistics), vol. 4:1, pages 59-90, November 2002.
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Software is available here.- Visualizing Class Structure of Multidimensional Data
I. S. Dhillon, D. S. Modha, and W. S. Spangler
Proceedings of the Thirtieth Symposium on the Interface: Computing Science and Statistics, Interface Foundation of North America, vol. 30, pages 488-493, Minneapolis, May 1998.
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Parallel Data Mining
- A Data Clustering Algorithm on Distributed Memory Multiprocessors
I. S. Dhillon and D. S. Modha
In Large-Scale Parallel Data Mining, Lecture Notes in Artificial Intelligence, vol. 1759, Springer-Verlag, pages 245-260, March 2000.
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(Also appears as IBM Research Report RJ 10134)
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The Metric Nearness Problem
- The Metric Nearness Problem
J. Brickell, I. S. Dhillon, S. Sra, and J. A. Tropp
SIAM Journal on Matrix Analysis and Applications, vol. 30:1, pages 375-396, April 2008.
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- Triangle Fixing Algorithms for the Metric Nearness Problem I. S. Dhillon, S. Sra, and J. A. Tropp
Eighteenth Annual Conference on Neural Information Processing Systems (NIPS), pages 361-368, December 2004.
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(Also appears as UTCS Technical Report #TR-04-22, June 2004. [Abstract & Download])- The Metric Nearness Problem with Applications
I. S. Dhillon, S. Sra, and J. A. Tropp
UTCS Technical Report #TR-03-23, July 2003. [Abstract & Download]
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PageRank
- Estimating the Global PageRank of Web Communities
J. Davis and I. S. Dhillon
Proceedings of the Twelfth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 116-125, August 2006.
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Adaptive Website Design
- Adaptive Website Design using Caching Algorithms
J. Brickell, I. S. Dhillon, and D. S. Modha
Twelfth ACM International Conference on Knowledge Discovery and Data Mining (KDD) (Workshop on Web Mining and Web Usage Analysis (WebKDD-2006)), August 2006.
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Clustering Gene Expression Data
- Co-clustering of Human Cancer Microarrays using Minimum Sum-Squared Residue Co-clustering
H. Cho and I. S. Dhillon
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), vol. 5:3, pages 385-400, July 2008.
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- Minimum Sum-Squared Residue Co-clustering of Gene Expression Data
H. Cho, I. S. Dhillon, Y. Guan, and S. Sra
Proceedings of the Fourth SIAM International Conference on Data Mining, pages 114-125, April 2004
Download: [pdf]- Diametrical Clustering for identifying Anti-Correlated Gene Clusters
I. S. Dhillon, E. M. Marcotte, and U. Roshan
Bioinformatics, vol. 19:13, pages 1612-1619, September 2003.
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(Also appears as UTCS Technical Report #TR-02-49, September 2002. [Abstract & Download])
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O(n^2) Eigenvalue/Eigenvector Computation for Symmetric Tridiagonals
- The Design and Implementation of the MRRR Algorithm
I. S. Dhillon, B. N. Parlett, and C. Vömel
ACM Transactions on Mathematical Software, vol. 32:4, pages 533-560, December 2006.
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- Glued Matrices and the MRRR Algorithm
I. S. Dhillon, B. N. Parlett, and C. Vömel
SIAM Journal on Scientific Computing, vol. 27:2, pages 496-510, October 2005.
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- A Parallel Eigensolver for Dense Symmetric Matrices based on Multiple Relatively Robust Representations
P. Bientinesi, I. S. Dhillon, and R. A. van de Geijn
SIAM Journal on Scientific Computing, vol. 27:1, pages 43-66, September 2005.
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(Also appears as UTCS Technical Report #TR-03-26, July 2003. [Abstract & Download])- Multiple Representations to Compute Orthogonal Eigenvectors of Symmetric Tridiagonal Matrices
I. S. Dhillon and B. N. Parlett
Linear Algebra and its Applications, vol. 387, pages 1-28, August 2004.
Download: [pdf]- Orthogonal Eigenvectors and Relative Gaps
I. S. Dhillon and B. N. Parlett
SIAM Journal on Matrix Analysis and Applications, vol. 25:3, pages 858-899, March 2004.
Download: [pdf]- Fernando's Solution to Wilkinson's Problem: An Application of Double Factorization
B. N. Parlett and I. S. Dhillon
Linear Algebra and its Applications, vol. 267, pages 247-279, 1997.
Download: [pdf]- A New O(N^2) Algorithm for the Symmetric Tridiagonal Eigenvalue/Eigenvector Problem
I. S. Dhillon
PhD. Thesis, University of California, Berkeley, Spring 1997.
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(Also available as UCB Tech. Report No. UCB//CSD-97-971.)
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Relative Perturbation Theory for Eigenvalue/Eigenvector Computation
- Relatively Robust Representations for Symmetric Tridiagonals
B. N. Parlett and I. S. Dhillon
Linear Algebra and its Applications, vol. 309, pages 121-151, November 2000.
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More Eigenvalue Problems
- Inner deflation of Symmetric, Tridiagonal Matrices
I. S. Dhillon and A. N. Malyshev
Linear Algebra and its Applications, vol. 358:1-3, pages 139-144, January 2003.
Download: [pdf]- Current inverse iteration software can fail
I. S. Dhillon
BIT Numerical Mathematics, 38:4, pages 685-704, December 1998.
Download: [pdf]- On the Correctness of Some Bisection-like Parallel Algorithms in Floating Point Arithmetic
J. W. Demmel, I. S. Dhillon, and H. Ren
Electronic Transactions of Numerical Analysis (ETNA), vol. 3, pages 116-140, December 1995.
Download: [pdf]- Application of a New Algorithm for the Symmetric Eigenproblem to Computational Quantum Chemistry
I. S. Dhillon, G. Fann, and B. N. Parlett
Proceedings of the Eighth SIAM Conference on Parallel Processing for Scientific Computing, Minneapolis, March 1997.
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Inverse Eigenvalue Problems in Wireless Communications
- Constructing Packings in Grassmannian Manifolds via Alternating Projections
I. S. Dhillon, R. W. Heath Jr., T. Strohmer, and J. A. Tropp
Experimental Mathematics, vol. 17:1, pages 9-35, 2008.
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- On the Existence of Equiangular Tight Frames
M. A. Sustik, J. A. Tropp, I. S. Dhillon, and R. W. Heath Jr.
Linear Algebra and its Applications, vol. 426:2-3, pages 619-635, October 2007.
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(A previous version appears as UTCS Technical Report #TR-04-32, August 2004. [Abstract & Download])- Generalized Finite Algorithms for Constructing Hermitian Matrices with Prescribed Diagonal and Spectrum
I. S. Dhillon, R. W. Heath Jr., M. A. Sustik, and J. A. Tropp
SIAM Journal on Matrix Analysis and Applications, vol. 27:1, pages 61-71, May 2005.
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(Also appears as UTCS Technical Report #TR-03-49, November 2003. [Abstract & Download])
- Designing Structured Tight Frames Via an Alternating Projection Method
J. A. Tropp, I. S. Dhillon, R. W. Heath Jr., and T. Strohmer
IEEE Transactions on Information Theory, vol. 51:1, pages 188-209, January 2005.
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(Also appears as ICES Report 03-50, UT, December 2003. [Abstract & Download])
- Finite-Step Algorithms for Constructing Optimal CDMA Signature Sequences
J. A. Tropp, I. S. Dhillon, and R. W. Heath Jr.
IEEE Transactions on Information Theory, vol. 50:11, pages 2916-2921, November 2004.
Download: [pdf]
(Also appears as WNCG-TR-2003-05-08, UT, June 2003. [Abstract & Download])
- Construction of Equiangular Signatures for Synchronous CDMA Systems
R. W. Heath Jr., J. A. Tropp, I. S. Dhillon, and T. Strohmer
Proceedings of IEEE International Symposium on Spread Spectrum Techniques and Applications, August 2004.
Download: [pdf]- Optimal CDMA Signatures: A Finite-Step Approach
J. A. Tropp, I. S. Dhillon, and R. W. Heath Jr.
Proceedings of IEEE International Symposium on Spread Spectrum Techniques and Applications, August 2004.
Download: [pdf]- CDMA Signature Sequences with Low Peak-To-Average Ratio via Alternating Projection
J. A. Tropp, I. S. Dhillon, R. W. Heath Jr., and T. Strohmer
Proceedings of the Thirty-Seventh IEEE Asilomar Conference on Signals, Systems, and Computers, pages 475-479, November 2003.
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Parallel Computation
- Practical Experience in the Numerical Dangers of Heterogeneous Computing
L. Blackford, A. Cleary, J. Demmel, I. S. Dhillon, J. Dongarra, S. Hammarling, A. Petitet, H. Ren, K. Stanley, and R. Whaley
ACM Transactions on Mathematical Software, vol. 23:2, pages 133-147, June 1997.
Download: [pdf]- ScaLAPACK Users' Guide
L. Blackford, J. Choi, A. Cleary, J. Demmel, I. S. Dhillon, J. Dongarra, S. Hammarling, G. Henry, A. Petitet, K. Stanley, D. Walker, and R.C. Whaley
SIAM, 1997.
Download: [HTML]- ScaLAPACK: A Linear Algebra Library for Message-Passing Computers
L. S. Blackford, J. Choi, A. Cleary, E. D'Azevedo, J. Demmel, I. S. Dhillon, J. Dongarra, S. Hammarling, G. Henry, A. Petitet, K. Stanley, D. Walker, and R. C. Whaley SIAM Conference on Parallel Processing, March 1997.
Download: [pdf]- ScaLAPACK: A Portable Linear Algebra Library for Distributed Memory Computers - Design Issues and Performance
J. Choi, J. Demmel, I. S. Dhillon, J. Dongarra, S. Ostrouchov, A. Petitet, K. Stanley, D. Walker, and R. C. Whaley
Computer Physics Communications, vol. 97, pages 1-15, August 1996.
Download: [pdf]
(Also available as LAPACK Working Note 95.)- ScaLAPACK: A Portable Linear Algebra Library for Distributed Memory Computers - Design Issues and Performance
L. Blackford, J. Choi, A. Cleary, J. Demmel, I. S. Dhillon, J. Dongarra, S. Hammarling, G. Henry, A. Petitet, K. Stanley, D. Walker, and R.C. Whaley
Proceedings of Supercomputing '96, 1996.
Download: [pdf]- Installation Guide for ScaLAPACK
J. Choi, J. Demmel, I. S. Dhillon, J. Dongarra, S. Ostrouchov, A. Petitet, K. Stanley, D. Walker, and R. C. Whaley
University of Tennessee Computer Science Technical Report, UT-CS-95-280, March 1995 (version 1.0), updated August 31, 2001 (version 1.7) --- also available as LAPACK Working Note 93.
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Novel Parallel Architectures
- An Overview of the Compilation Process for a New Parallel Architecture
I. S. Dhillon, N, K. Karmarkar, and K. G. Ramakrishnan
Supercomputing Symposium '91, pages 471-486, New Brunswick, Canada, June 1991.
Download: [pdf]- Performance Analysis of a Proposed Parallel Architecture on Matrix Vector Multiply Like Routines
I. S. Dhillon, N. K. Karmarkar, and K. G. Ramakrishnan
Technical Memorandum 11216-901004-13TM, AT&T Bell Laboratories, Murray Hill, NJ, 1990.
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Miscellaneous
- Computation of the Singular Value Decomposition
A. K. Cline and I. S. Dhillon
Invited book chapter in Handbook of Linear Algebra, CRC Press, pages 45-1--45-13, 2006.
Download: [pdf]- Reliable computation of the Condition Number of a Tridiagonal Matrix in O(n) Time
I. S. Dhillon
SIAM Journal on Matrix Analysis and Applications, vol. 19:3, pages 776-796, July 1998.
Download: [pdf]- Efficient Computation of the Singular Value Decomposition with Applications to Least Squares Problems
M. Gu, J. W. Demmel, I. S. Dhillon
Technical Report LBL-36201, Lawrence Berkeley National Laboratory, October 1994.
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