2022

• Faster non-convex federated learning via global and local momentum (arXiv, software)
  R. Das, A. Acharya, A. Hashemi, S. Sanghavi, I. Dhillon, U. Topcu.
  To appear in Conference on Uncertainity in Artificial Intelligence (UAI) (UAI), 2022. (Spotlight)
• Robust Training in High Dimensions via Block Coordinate Geometric Median Descent (arXiv, slides, poster, software, code)
  A. Acharya, A. Hashemi, P. Jain, S. Sanghavi, I. Dhillon, U. Topcu.
  In International Conference on Artificial Intelligence and Statistics (AISTATS), March 2022.

2021

• On the Benefits of Multiple Gossip Steps in Communication-Constrained Decentralized Federated Learning (pdf, software)
  A. Hashemi, A. Acharya, R. Das, H. Vikalo, S. Sanghavi, I. Dhillon.
  IEEE Transactions on Parallel and Distributed Systems (IEEE TPDS) , December 2021.

2019

• AutoAssist: A Framework to Accelerate Training of Deep Neural Networks
  J. Zhang, H. Yu, I. Dhillon.
  To appear in Neural Information Processing Systems (NIPS), December 2019.
• Think Globally, Act Locally: A Deep Neural Network Approach to High-Dimensional Time Series Forecasting
  R. Sen, H. Yu, I. Dhillon.
  To appear in Neural Information Processing Systems (NIPS), December 2019.
• Similarity preserving representation learning for time series analysis (pdf, software)
  Q. Lei, J. Yi, R. Vaculin, L. Wu, I. Dhillon.
  In International Joint Conference on Artificial Intelligence (IJCAI), pp. 2845-2851, August 2019.
• Discrete adversarial attacks and submodular optimization with applications to text classification (pdf, software)
  Q. Lei, L. Wu, P. Chen, A. Dimakis, I. Dhillon, M. Witbrock.
  In The Conference on Systems and Machine Learning (SysML), April 2019. (Oral)
• Extreme stochastic variational inference: distributed and asynchronous
  J. Zhang, P. Raman, S. Ji, S. Vishwanathan, I. Dhillon.
  In International Conference on Artificial Intelligence and Statistics (AISTATS), 2019.
• Inverting Deep Generative models, One layer at a time (pdf, software)
  Q. Lei, A. Jalal, I. Dhillon, A. Dimakis.
  To appear in Neural Information Processing Systems (NIPS), 2019.
• Online embedding compression for text classification using low rank matrix factorization (pdf, software)
  A. Acharya, R. Goel, A. Metallinou, I. Dhillon.
  In the AAAI Conference on Artificial Intelligence (AAAI), pp. 6196-6203, 2019.
• Parallel Asynchronous Stochastic Coordinate Descent with Auxiliary Variables
  H. Yu, C. Hsieh, I. Dhillon.
  In International Conference on Artificial Intelligence and Statistics (AISTATS), 2019.
• Primal-Dual Block Frank-Wolfe (pdf, software)
  Q. Lei, J. Zhuo, I. Dhillon, C. Caramanis, A. Dimakis.
  To appear in Neural Information Processing Systems (NIPS), 2019.
• Provable Non-linear Inductive Matrix Completion
  K. Zhong, Z. Song, P. Jain, I. Dhillon.
  To appear in Neural Information Processing Systems (NIPS), 2019.
• The limitations of adversarial training and the blind-spot attack
  H. Zhang, H. Chen, Z. Song, D. Boning, I. Dhillon, C. Hsieh.
  In International Conference on Learning Representations, 2019.

2018

• Non-exhaustive, Overlapping Clustering (pdf, software)
  J. Whang, Y. Hou, D. Gleich, I. Dhillon.
  IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI) 41(11), pp. 2644–2659, August 2018.
• Learning long term dependencies via Fourier recurrent units (pdf, arXiv, software)
  J. Zhang, Y. Lin, Z. Song, I. Dhillon.
  In International Conference on Machine Learning (ICML), pp. 5810–5818, July 2018.
• Stabilizing Gradients for Deep Neural Networks via Efficient SVD Parameterization (pdf, arXiv, software)
  J. Zhang, Q. Lei, I. Dhillon.
  In International Conference on Machine Learning (ICML), pp. 5801–5809, July 2018.
• Towards Fast Computation of Certified Robustness for ReLU Networks (pdf, software)
  T. Weng, H. Zhang, H. Chen, Z. Song, C. Hsieh, D. Boning, I. Dhillon, L. Daniel.
  In International Conference on Machine Learning (ICML), pp. 5273–5282, July 2018. (Oral)
• Fast Asynchronous Anti-TrustRank forWeb Spam Detection
  J. Whang, Y. Jung, I. Dhillon, S. Kang, J. Lee.
  WSDM workshop on Misinformation and Misbehavior Mining on the Web (MIS2), 2018.

2017

• A Greedy Approach for Budgeted Maximum Inner Product Search (pdf, software)
  H. Yu, C. Hsieh, Q. Lei, I. Dhillon.
  In Neural Information Processing Systems (NIPS), December 2017.
• Non-Exhaustive, Overlapping Co-Clustering
  J. Whang, I. Dhillon.
  In ACM Conference on Information and Knowledge Management (CIKM), November 2017.
• Doubly Greedy Primal-Dual Coordinate Methods for Sparse Empirical Risk Minimization (pdf, software)
  Q. Lei, I. Yen, C. Wu, P. Ravikumar, I. Dhillon.
  In International Conference on Machine Learning (ICML), pp. 8, August 2017.
• Recovery Guarantees for One-hidden-layer Neural Networks (pdf, arXiv, software)
  K. Zhong, Z. Song, P. Jain, P. Bartlett, I. Dhillon.
  In International Conference on Machine Learning (ICML), pp. 4140-4149, August 2017. (Oral)
• A Review of Multivariate Distributions for Count Data Derived from the Poisson Distribution (arXiv, software, code)
  D. Inouye, E. Yang, G. Allen, P. Ravikumar.
  WIREs Computational Statistics , May 2017.
• Fast Classification with Binary Prototypes (pdf, software)
  K. Zhong, R. Guo, S. Kumar, B. Yan, D. Simcha, I. Dhillon.
  In International Conference on Artificial Intelligence and Statistics (AISTATS), 2017.
• Greedy Direction Method of Multiplier for MAP Inference of Large Output Domain (pdf, software)
  X. Huang, I. Yen, R. Zhang, Q. Huang, P. Ravikumar, I. Dhillon.
  In International Conference on Artificial Intelligence and Statistics (AISTATS), April 2017.
• Rank Aggregation and Prediction with Item Features (pdf, software)
  K. Chiang, C. Hsieh, I. Dhillon.
  In International Conference on Artificial Intelligence and Statistics (AISTATS), April 2017.
• Scalable Convex Multiple Sequence Alignment via Entropy-Regularized Dual Decomposition (pdf, software)
  J. Zhang, I. Yen, P. Ravikumar, I. Dhillon.
  In International Conference on Artificial Intelligence and Statistics (AISTATS), April 2017.
• A Unified Algorithm for One-Cass Structured Matrix Factorization with Side Information (pdf, software)
  H. Yu, H. Huang, I. Dhillon, C. Lin.
  In the AAAI Conference on Artificial Intelligence (AAAI), 2017.
• Communication-Efficient Distributed Block Minimization for Nonlinear Kernel Machines (pdf, software)
  C. Hsieh, S. Si, I. Dhillon.
  In ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2017.
• Memory Efficient Kernel Approximation (pdf, software)
  S. Si, C. Hsieh, I. Dhillon.
  Journal of Machine Learning Research (JMLR) 18: 20:1-20:32, 2017.
• Partial Hard Thresholding (pdf, software)
  P. Jain, A. Tewari, I. Dhillon.
  IEEE Transactions on Information Theory 63(5): 3029-3038, 2017.

2016

• Asynchronous Parallel Greedy Coordinate Descent (pdf, software)
  Y. You, X. Lian, J. Liu, H. Yu, I. Dhillon, J. Demmel, C. Hsieh.
  In Neural Information Processing Systems (NIPS), December 2016.
• Coordinate-wise Power Method (pdf, software, code)
  Q. Lei, K. Zhong, I. Dhillon.
  To appear in Neural Information Processing Systems (NIPS), December 2016.
• Dual Decomposed Learning with Factorwise Oracle for Structural SVM with Large Output Domain (pdf, software)
  I. Yen, X. Huang, K. Zhong, R. Zhang, P. Ravikumar, I. Dhillon.
  In Neural Information Processing Systems (NIPS), December 2016.
• Mixed Linear Regression with Multiple Components (pdf, software)
  K. Zhong, P. Jain, I. Dhillon.
  In Neural Information Processing Systems (NIPS), December 2016.
• Structured Sparse Regression via Greedy Hard Thresholding (pdf, arXiv, software)
  P. Jain, N. Rao, I. Dhillon.
  In Neural Information Processing Systems (NIPS), pp. 1516-1524, December 2016.
• Temporal Regularized Matrix Factorization for High-dimensional Time Series Prediction (pdf, software, code)
  H. Yu, N. Rao, I. Dhillon.
  In Neural Information Processing Systems (NIPS), pp. 847-855, December 2016.
• Goal-Directed Inductive Matrix Completion (pdf, slides, software)
  S. Si, K. Chiang, C. Hsieh, N. Rao, I. Dhillon.
  In ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pp. 1165–1174, August 2016. (Oral)
• Efficient and Non-Convex Coordinate Descent for Symmetric Nonnegative Matrix Factorization (pdf, software, code)
  A. Vandaele, N. Gillis, Q. Lei, K. Zhong, I. Dhillon.
  IEEE Transactions on Signal Processing 64(21), pp. 5571 – 5584, 2016.
• Square Root Graphical Models: Multivariate Generalizations of Univariate Exponential Families that Permit Positive Dependencies (pdf, arXiv, poster, software, code)
  D. Inouye, P. Ravikumar, I. Dhillon.
  In International Conference on Machine Learning (ICML), pp. 2445-2453, June 2016. (Oral)
• Computationally Efficient Nystrom Approximation using Fast Transforms (pdf, slides, software)
  S. Si, C. Hsieh, I. Dhillon.
  In International Conference on Machine Learning (ICML), pp. 2655-2663, June 2016.
• A Convex Atomic-Norm Approach to Multiple Sequence Alignment and Motif Discovery (pdf, slides, poster, software)
  I. Yen, X. Lin, J. Zhang, P. Ravikumar, I. Dhillon.
  In International Conference on Machine Learning (ICML), June 2016. (Oral)
• A Primal and Dual Sparse Approach to Extreme Classification (pdf, slides, poster, software, code)
  I. Yen, X. Huang, K. Zhong, P. Ravikumar, I. Dhillon.
  In International Conference on Machine Learning (ICML), June 2016. (Oral)
• Robust Principal Component Analysis with Side Information (pdf, software)
  K. Chiang, C. Hsieh, I. Dhillon.
  In International Conference on Machine Learning (ICML), pp. 2291–2299, June 2016.
• Fast Multiplier Methods to Optimize Non-exhaustive, Overlapping Clustering (pdf, software)
  Y. Hou, J. Whang, D. Gleich, I. Dhillon.
  In SIAM International Conference on Data Mining (SDM), pp. 297–305, May 2016. (Oral)
• Overlapping Community Detection Using Neighborhood-Inflated Seed Expansion (pdf, software)
  J. Whang, D. Gleich, I. Dhillon.
  IEEE Transactions on Knowledge and Data Engineering (TKDE) 28(5), pp. 1272–1284, 2016.
• Nomadic Computing for Big Data Analytics
  H. Yu, C. Hsieh, H. Yun, S. Vishwanathan, I. Dhillon.
  IEEE Computer (IEEE Computer) 49(4), pp. 52–60, 2016.

2015

• Consistent Multilabel Classification
  O. Koyejo, N. Natarajan, P. Ravikumar, I. Dhillon.
  In Neural Information Processing Systems (NIPS), pp. 3303–3311, December 2015.
• PU Matrix Completion with Graph Information
  N. Natarajan, N. Rao, I. Dhillon.
  International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), December 2015.
• Collaborative Filtering with Graph Information: Consistency and Scalable Methods (pdf, software, code)
  N. Rao, H. Yu, P. Ravikumar, I. Dhillon.
  In Neural Information Processing Systems (NIPS), pp. 2098–2106, December 2015. (Spotlight)
• Matrix Completion with Noisy Side Information (pdf, software)
  K. Chiang, C. Hsieh, I. Dhillon.
  In Neural Information Processing Systems (NIPS), pp. 3447–3455, December 2015. (Spotlight)
• Beyond Sub-Gaussian Measurements: High-Dimensional Structured Estimation with Sub-Exponential Designs (pdf, software)
  V. Sivakumar, A. Banerjee, P. Ravikumar.
  In Neural Information Processing Systems (NIPS), pp. 2206-2214, December 2015.
• Closed-form Estimators for High-dimensional Generalized Linear Models (pdf, software)
  E. Yang, A. Lozano, P. Ravikumar.
  To appear in Neural Information Processing Systems (NIPS), pp. 586-594, December 2015. (Spotlight)
• Sparse Linear Programming via Primal and Dual Augmented Coordinate Descent (pdf, software, code)
  I. Yen, K. Zhong, C. Hsieh, P. Ravikumar, I. Dhillon.
  In Neural Information Processing Systems (NIPS), December 2015.
• Fast Classification Rates for High-dimensional Gaussian Generative Models (pdf, software)
  T. Li, A. Prasad, P. Ravikumar.
  In Neural Information Processing Systems (NIPS), pp. 1054-1062, December 2015.
• Fixed-Length Poisson MRF: Adding Dependencies to the Multinomial (pdf, poster, software, code)
  D. Inouye, P. Ravikumar, I. Dhillon.
  In Neural Information Processing Systems (NIPS), pp. 3195-3203, December 2015.
• Graphical Models via Univariate Exponential Family Distributions (pdf, arXiv, software)
  E. Yang, P. Ravikumar, G. Allen, Z. Liu.
  Journal of Machine Learning Research (JMLR) , pp. 3813-3847, December 2015.
• Tumblr Blog Recommendation with Boosted Inductive Matrix Completion (pdf, software)
  D. Shin, S. Cetintas, K. Lee, I. Dhillon.
  In ACM Conference on Information and Knowledge Management (CIKM), pp. 203–212, October 2015.
• Efficient Matrix Sensing Using Rank-1 Gaussian Measurements (pdf, software)
  K. Zhong, P. Jain, I. Dhillon.
  In International Conference on Algorithmic Learning Theory (ALT), pp. 3-18, October 2015.
• Non-exhaustive, Overlapping Clustering via Low-Rank Semidefinite Programming (pdf, slides, software)
  Y. Hou, J. Whang, D. Gleich, I. Dhillon.
  In ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pp. 427–436, August 2015. (Oral)
• Scalable Data-driven PageRank: Algorithms, System Issues, and Lessons Learned (pdf, software)
  J. Whang, A. Lenharth, I. Dhillon, K. Pingali.
  In International European Conference on Parallel and Distributed Computing (Euro-Par), pp. 438–450, August 2015. (Oral)
• A Convex Exemplar-based Approach to MAD-Bayes Dirichlet Process Mixture Models (pdf, slides, software)
  I. Yen, X. Lin, K. Zhong, P. Ravikumar, I. Dhillon.
  In International Conference on Machine Learning (ICML), pp. 2418-2426, July 2015.
• PASSCoDe: Parallel ASynchronous Stochastic dual Co-ordinate Descent (pdf, software)
  C. Hsieh, H. Yu, I. Dhillon.
  In International Conference on Machine Learning (ICML), pp. 2370-2379, July 2015.
• Distributional Rank Aggregation, and an Axiomatic Analysis (pdf, software)
  A. Prasad, H. Pareek, P. Ravikumar.
  In International Conference on Machine Learning (ICML), July 2015.
• Preference Completion: Large-scale Collaborative Ranking from Pairwise Comparisons (pdf, software)
  D. Park, J. Neeman, J. Zhang, S. Sanghavi, I. Dhillon.
  In International Conference on Machine Learning (ICML), pp. 1907-1916, July 2015.
• PU Learning for Matrix Completion (pdf, software)
  C. Hsieh, N. Natarajan, I. Dhillon.
  In International Conference on Machine Learning (ICML), pp. 2445-2453, July 2015.
• Vector-Space Markov Random Fields via Exponential Families (pdf, arXiv, software)
  W. Tansey, O. Padilla, A. Suggala, P. Ravikumar.
  In International Conference on Machine Learning (ICML), pp. 684-692, July 2015.
• A Scalable Asynchronous Distributed Algorithm for Topic Modeling (pdf, arXiv, software, code)
  H. Yu, C. Hsieh, H. Yun, S. Vishwanathan, I. Dhillon.
  In International World Wide Web Conference (WWW), pp. 1340-1350, May 2015. (Oral)
• Optimal Decision-Theoretic Classification Using Non-Decomposable Performance Metrics (pdf, arXiv, software)
  N. Natarajan, O. Koyejo, P. Ravikumar, I. Dhillon.
  arXiv (arXiv) 1505.01802, May 2015.
• Non-exhaustive, Overlapping k-means (pdf, software)
  J. Whang, I. Dhillon, D. Gleich.
  In SIAM International Conference on Data Mining (SDM), pp. 936–944, May 2015.
• Learning-based Analytical Cross-Platform Performance Prediction (pdf, software)
  X. Zheng, P. Ravikumar, L. John, A. Gerstlauer.
  In International Conference on Embedded Computer Systems: Architectures, Modeling, and Simulation, 2015.
• Sparsistency of l1-Regularized M-Estimators (pdf, arXiv, software)
  Y. Li, J. Scarlett, P. Ravikumar, V. Cevher.
  In International Conference on Artificial Intelligence and Statistics (AISTATS), 2015. (Oral)
• Tracking with Ranked Signals (pdf, software)
  T. Li, H. Pareek, P. Ravikumar, D. Balwada, K. Speer.
  In Conference on Uncertainity in Artificial Intelligence (UAI) (UAI), 2015. (Oral)

2014

• Predicting Growth Conditions from Internal Metabolic Fluxes in an In-Silico Model of E. coli (pdf, software)
  V. Sridhara, A. Meyer, P. Rai, J. Barrick, P. Ravikumar, D. Segrè, C. Wilke.
  PLoS ONE 9(12), pp. e114608, December 2014.
• Proximal Quasi-Newton for Computationally Intensive L1-regularized M-estimators (pdf, software, code)
  K. Zhong, I. Yen, I. Dhillon, P. Ravikumar.
  In Neural Information Processing Systems (NIPS), pp. 2375-2383, December 2014.
• A Representation Theory for Ranking Functions (pdf, software)
  H. Pareek, P. Ravikumar.
  In Neural Information Processing Systems (NIPS), December 2014.
• Consistent Binary Classification with Generalized Performance Metrics (pdf, poster, software)
  N. Natarajan, O. Koyejo, P. Ravikumar, I. Dhillon.
  In Neural Information Processing Systems (NIPS), pp. 2744-2752, December 2014.
• Constant Nullspace Strong Convexity and Fast Convergence of Proximal Methods under High-Dimensional Settings (pdf, software)
  I. Yen, C. Hsieh, P. Ravikumar, I. Dhillon.
  In Neural Information Processing Systems (NIPS), pp. 1008-1016, December 2014.
• Elementary Estimators for Graphical Models (pdf, software)
  E. Yang, A. Lozano, P. Ravikumar.
  In Neural Information Processing Systems (NIPS), December 2014.
• Fast Prediction for Large-Scale Kernel Machines (pdf, software)
  C. Hsieh, S. Si, I. Dhillon.
  In Neural Information Processing Systems (NIPS), pp. 3689-3697, December 2014.
• Multi-Scale Spectral Decomposition of Massive Graphs (pdf, software)
  S. Si, D. Shin, I. Dhillon, B. Parlett.
  In Neural Information Processing Systems (NIPS), pp. 2798-2806, December 2014.
• On the Information Theoretic Limits of Learning Ising Models (arXiv, software)
  R. Tandon, K. Shanmugam, A. Dimakis, P. Ravikumar.
  To appear in Neural Information Processing Systems (NIPS), December 2014.
• QUIC & DIRTY: A Quadratic Approximation Approach for Dirty Statistical Models (pdf, software)
  C. Hsieh, I. Dhillon, P. Ravikumar, S. Becker, P. Olsen.
  In Neural Information Processing Systems (NIPS), pp. 2006–2014, December 2014.
• Sparse Random Feature Algorithm as Coordinate Descent in Hilbert Space (pdf, software)
  I. Yen, T. Lin, S. Lin, P. Ravikumar, I. Dhillon.
  In Neural Information Processing Systems (NIPS), pp. 2456-2464, December 2014.
• Capturing Semantically Meaningful Word Dependencies with an Admixture of Poisson MRFs (pdf, poster, software, code)
  D. Inouye, P. Ravikumar, I. Dhillon.
  In Neural Information Processing Systems (NIPS), pp. 3158-3166, December 2014.
• Parallel Matrix Factorization for Recommender Systems (pdf, software)
  H. Yu, C. Hsieh, S. Si, I. Dhillon.
  Knowledge and Information Systems (KAIS) 41(3), pp. 793-819, December 2014.
• QUIC: Quadratic Approximation for Sparse Inverse Covariance Matrix Estimation (pdf, software)
  C. Hsieh, M. Sustik, I. Dhillon, P. Ravikumar.
  Journal of Machine Learning Research (JMLR), October 2014.
• NOMAD: Non-locking, stOchastic Multi-machine algorithm for Asynchronous and Decentralized matrix completion (pdf, software)
  H. Yun, H. Yu, C. Hsieh, S. Vishwanathan, I. Dhillon.
  In International Conference on Very Large Data Bases (VLDB), pp. 975-986, July 2014.
• Large-scale Multi-label Learning with Missing Labels (pdf, software)
  H. Yu, P. Jain, P. Kar, I. Dhillon.
  In International Conference on Machine Learning (ICML), pp. 593–601, June 2014.
• Elementary Estimators for High-Dimensional Linear Regression (pdf, software)
  E. Yang, A. Lozano, P. Ravikumar.
  In International Conference on Machine Learning (ICML), 2014. (Oral)
• Elementary Estimators for Sparse Covariance Matrices and other Structured Moments (pdf, software)
  E. Yang, A. Lozano, P. Ravikumar.
  In International Conference on Machine Learning (ICML), 2014. (Oral)
• A Divide-and-Conquer Solver for Kernel Support Vector Machines (pdf, software, code)
  C. Hsieh, S. Si, I. Dhillon.
  In International Conference on Machine Learning (ICML), pp. 566-574, June 2014.
• Learning Graphs with a Few Hubs (pdf, software)
  R. Tandon, P. Ravikumar.
  In International Conference on Machine Learning (ICML), June 2014.
• Memory Efficient Kernel Approximation (pdf, slides, software, code)
  S. Si, C. Hsieh, I. Dhillon.
  In International Conference on Machine Learning (ICML), pp. 701-709, June 2014.
• Inductive matrix completion for predicting gene-disease associations (pdf, software)
  N. Natarajan, I. Dhillon.
  Bioinformatics 30(12), pp. i60-i68, June 2014.
• Exponential Family Matrix Completion under Structural Constraint (pdf, software)
  S. Gunasekar, P. Ravikumar, J. Ghosh.
  In International Conference on Machine Learning (ICML), June 2014.
• Admixture of Poisson MRFs: A Topic Model with Word Dependencies (pdf, slides, poster, software, code)
  D. Inouye, P. Ravikumar, I. Dhillon.
  In International Conference on Machine Learning (ICML), pp. 683-691, June 2014.
• Prediction and Clustering in Signed Networks: A Local to Global Perspective (pdf, software)
  K. Chiang, C. Hsieh, N. Natarajan, A. Tewari, I. Dhillon.
  Journal of Machine Learning Research (JMLR) 15, pp. 1177-1213, March 2014.
• Mixed Graphical Models via Exponential Families (pdf, software)
  E. Yang, Y. Baker, P. Ravikumar, G. Allen, Z. Liu.
  In International Conference on Artificial Intelligence and Statistics (AISTATS), 2014. (Oral)

2013

• Dirty Statistical Models (pdf, software)
  E. Yang, P. Ravikumar.
  In Neural Information Processing Systems (NIPS), 2013.
• Conditional Random Fields via Univariate Exponential Families (pdf, software)
  E. Yang, P. Ravikumar, G. Allen, Z. Liu.
  In Neural Information Processing Systems (NIPS), December 2013.
• On Poisson Graphical Models (pdf, software)
  E. Yang, P. Ravikumar, G. Allen, Z. Liu.
  In Neural Information Processing Systems (NIPS), December 2013.
• BIG & QUIC: Sparse Inverse Covariance Estimation for a Million Variables (pdf, software)
  C. Hsieh, M. Sustik, I. Dhillon, P. Ravikumar, R. Poldrack.
  In Neural Information Processing Systems (NIPS), December 2013. (Oral)
• Large Scale Distributed Sparse Precision Estimation (pdf, software)
  H. Wang, C. Hsieh, A. Banerjee, P. Ravikumar, I. Dhillon.
  In Neural Information Processing Systems (NIPS), December 2013.
• Learning with Noisy Labels (pdf, poster, software)
  N. Natarajan, A. Tewari, I. Dhillon, P. Ravikumar.
  In Neural Information Processing Systems (NIPS), pp. 1196-1204, December 2013.
• Stochastic Blockmodel with Cluster Overlap, Relevance Selection, and Similarity-Based Smoothing (pdf, slides, software)
  J. Whang, P. Rai, I. Dhillon.
  In IEEE International Conference on Data Mining (ICDM), pp. 817 – 826, December 2013. (Oral)
• Overlapping Community Detection Using Seed Set Expansion (pdf, slides, software)
  J. Whang, D. Gleich, I. Dhillon.
  In ACM Conference on Information and Knowledge Management (CIKM), pp. 2099-2108, October 2013. (Oral)
• Which app will you use next? Collaborative Filtering with Interactional Context (pdf, software)
  N. Natarajan, D. Shin, I. Dhillon.
  In ACM Conference on Recommender Systems (RecSys), pp. 201-208, October 2013.
• On the Difficulty of Learning Power Law Graphical Models (pdf, software)
  R. Tandon, P. Ravikumar.
  In IEEE International Symposium on Information Theory (ISIT), 2013.
• Prediction and Validation of Gene-Disease Associations using Methods Inspired by Social Network Analyses (pdf, software)
  U. Singh-Blom, N. Natarajan, A. Tewari, J. Woods, I. Dhillon, E. Marcotte.
  PLoS ONE 8(5), May 2013.
  (e58977)
• A Dirty Model for Multiple Sparse Regression (pdf, software)
  A. Jalali, P. Ravikumar, S. Sanghavi.
  IEEE Transactions on Information Theory 59(12), pp. 7947-7968, 2013.
• Human Boosting (pdf, software)
  H. Pareek, P. Ravikumar.
  In International Conference on Machine Learning (ICML), 2013.
• On Robust Estimation of High Dimensional Generalized Linear Models (pdf, software)
  E. Yang, A. Tewari, P. Ravikumar.
  In International Joint Conference on Artificial Intelligence (IJCAI), 2013.

2012

• A Divide-and-Conquer Method for Sparse Inverse Covariance Estimation (pdf, software)
  C. Hsieh, I. Dhillon, P. Ravikumar, A. Banerjee.
  In Neural Information Processing Systems (NIPS), pp. 2339-2347, December 2012.
• Scalable and Memory-Efficient Clustering of Large-Scale Social Networks (pdf, slides, software)
  J. Whang, X. Sui, I. Dhillon.
  In IEEE International Conference on Data Mining (ICDM), pp. 705-714, December 2012. (Oral)
• Graphical Models via Generalized Linear Models (pdf, software)
  E. Yang, P. Ravikumar, G. Allen, Z. Liu.
  In Neural Information Processing Systems (NIPS), 2012. (Oral)
• Scalable Coordinate Descent Approaches to Parallel Matrix Factorization for Recommender Systems (pdf, software)
  H. Yu, C. Hsieh, S. Si, I. Dhillon.
  In IEEE International Conference on Data Mining (ICDM), pp. 765-774, December 2012. (Oral)
• Parallel Clustered Low-rank Approximation of Graphs and Its Application to Link Prediction (pdf, software)
  X. Sui, T. Lee, J. Whang, B. Savas, S. Jain, K. Pingali, I. Dhillon.
  International Workshop on Languages and Compilers for Parallel Computing (LCPC), pp. 76-95, October 2012. (Oral)
• Scalable Clustering of Signed Networks using Balance Normalized Cut (pdf, slides, software)
  K. Chiang, J. Whang, I. Dhillon.
  In ACM Conference on Information and Knowledge Management (CIKM), pp. 615-624, October 2012. (Oral)
• Multi-Scale Link Prediction (pdf, software)
  D. Shin, S. Si, I. Dhillon.
  In ACM Conference on Information and Knowledge Management (CIKM), pp. 215-224, October 2012.
• Low-Rank Modeling of Signed Networks (pdf, software)
  C. Hsieh, K. Chiang, I. Dhillon.
  In ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), August 2012.
• Clustered Embedding of Massive Social Networks (pdf, software)
  H. Song, B. Savas, T. Cho, V. Dave, Z. Lu, I. Dhillon, Y. Zhang, L. Qui.
  In ACM SIGMETRICS/Performance Joint International Conference on Measurement and Modeling of Computer Systems (SIGMETRICS/Performance), pp. 331-342, June 2012.
• Metric and Kernel Learning using a Linear Transformation (pdf, software)
  P. Jain, B. Kulis, J. Davis, I. Dhillon.
  Journal of Machine Learning Research (JMLR) 13, pp. 519-547, March 2012.
• A unified framework for high-dimensional analysis of M-estimators with decomposable regularizers (pdf, software)
  S. Negahban, P. Ravikumar, M. Wainwright, B. Yu.
  Statistical Science 27(4), pp. 538-557, 2012.
• High-dimensional Sparse Inverse Covariance Estimation using Greedy Methods (pdf, software)
  A. Jalali, C. Johnson, P. Ravikumar.
  In International Conference on Artificial Intelligence and Statistics (AISTATS), 2012.
• Information-theoretic lower bounds on the oracle complexity of convex optimization (pdf, software)
  A. Agarwal, P. Bartlett, P. Ravikumar, M. Wainwright.
  IEEE Transactions on Information Theory 58(5), pp. 3235-3249, 2012.
• Perturbation based Large Margin Approach for Ranking (pdf, software)
  E. Yang, A. Tewari, P. Ravikumar.
  In International Conference on Artificial Intelligence and Statistics (AISTATS), 2012.
• A Non-monotonic Method for Large-scale Nonnegative Least Squares (pdf, software)
  D. Kim, S. Sra, I. Dhillon.
  Optimization Methods and Software, 2012.
• On a Zero-Finding Problem involving the Matrix Exponential (pdf, software)
  M. Sustik, I. Dhillon.
  SIAM Journal of Matrix Analysis and Applications (SIMAX) 33(4), pp. 1237-1249, 2012.

2011

• Greedy Algorithms for Structurally Constrained High Dimensional Problems (pdf, software)
  A. Tewari, P. Ravikumar, I. Dhillon.
  In Neural Information Processing Systems (NIPS), December 2011.
• Nearest Neighbor based Greedy Coordinate Descent (pdf, software)
  I. Dhillon, P. Ravikumar, A. Tewari.
  In Neural Information Processing Systems (NIPS), December 2011.
• Orthogonal Matching Pursuit with Replacement (pdf, software)
  P. Jain, A. Tewari, I. Dhillon.
  In Neural Information Processing Systems (NIPS), December 2011.
• Sparse Inverse Covariance Matrix Estimation using Quadratic Approximation (pdf, software)
  C. Hsieh, M. Sustik, I. Dhillon, P. Ravikumar.
  In Neural Information Processing Systems (NIPS), December 2011.
• Scalable Affiliation Recommendation using Auxiliary Networks (pdf, software)
  V. Vasuki, N. Natarajan, Z. Lu, B. Savas, I. Dhillon.
  ACM Transactions on Intelligent Systems and Technology (TIST) 3(1), October 2011.
• Exploiting Longer Walks for Link Prediction in Signed Network (pdf, software)
  K. Chiang, I. Dhillon, N. Natarajan, A. Tewari.
  In ACM Conference on Information and Knowledge Management (CIKM), pp. 1157-1162, October 2011.
• Fast Coordinate Descent Methods with Variable Selection for Non-negative Matrix Factorization (pdf, software)
  C. Hsieh, I. Dhillon.
  In ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pp. 1064-1072, August 2011.
• Clustered Low Rank Approximation of Graphs in Information Science Applications (pdf, software)
  B. Savas, I. Dhillon.
  In SIAM International Conference on Data Mining (SDM), pp. 164-175, April 2011.
• On Learning Discrete Graphical Models using Group-Sparse Regularization (pdf, software)
  A. Jalali, P. Ravikumar, V. Vasuki, S. Sanghavi.
  In International Conference on Artificial Intelligence and Statistics (AISTATS), April 2011.
• High dimensional covariance estimation by minimizing l1-penalized log-determinant divergence (pdf, software)
  P. Ravikumar, M. Wainwright, B. Yu, G. Raskutti.
  Electronic Journal of Statistics (EJS) 5, pp. 935-980, 2011.
• On NDCG Consistency of Listwise Ranking Methods (pdf, software)
  P. Ravikumar, A. Tewari, E. Yang.
  In International Conference on Artificial Intelligence and Statistics (AISTATS), 2011.
• On the Use of Variational Inference for Learning Discrete Graphical Models (pdf, software)
  E. Yang, P. Ravikumar.
  In International Conference on Machine Learning (ICML), 2011. (Oral)
• On Learning Discrete Graphical Models using Greedy Methods (pdf, software)
  A. Jalali, C. Johnson, P. Ravikumar.
  In Neural Information Processing Systems (NIPS), 2011.
• Encoding and Decoding V1 fMRI Responses to Natural Images with Sparse Nonparametric Models (pdf, arXiv, software)
  V. Vu, P. Ravikumar, T. Naselaris, K. Kay, J. Gallant, B. Yu.
  Annals of Applied Statistics 5, pp. 1159-1182, 2011.

2010

• A Dirty Model for Multi-task Learning (pdf, software)
  A. Jalali, P. Ravikumar, S. Sanghavi, C. Ruan.
  In Neural Information Processing Systems (NIPS), December 2010.
• Guaranteed Rank Minimization via Singular Value Projection (pdf, software)
  R. Meka, P. Jain, I. Dhillon.
  In Neural Information Processing Systems (NIPS), pp. 937-945, December 2010.
• Inductive Regularized Learning of Kernel Functions (pdf, software)
  P. Jain, B. Kulis, I. Dhillon.
  In Neural Information Processing Systems (NIPS), pp. 946-954, December 2010.
• Supervised Link Prediction Using Multiple Sources (pdf, software)
  Z. Lu, B. Savas, W. Tang, I. Dhillon.
  In IEEE International Conference on Data Mining (ICDM), pp. 923-928, December 2010.
• Tackling Box-Constrained Optimization Via a New Projected Quasi-Newton Approach (pdf, software)
  D. Kim, S. Sra, I. Dhillon.
  SIAM Journal on Scientific Computing 30(6), pp. 3548-3563, December 2010.
• Affiliation Recommendation using Auxiliary Networks (pdf, software)
  V. Vasuki, N. Natarajan, Z. Lu, I. Dhillon.
  In ACM Conference on Recommender Systems (RecSys), pp. 103-110, September 2010. (Oral)
• A Scalable Trust-region Algorithm with Application to Mixed-Norm Regression (pdf, software)
  D. Kim, S. Sra, I. Dhillon.
  In International Conference on Machine Learning (ICML), pp. 519-526, June 2010.
• Message-passing for Graph-structured Linear Programs: Proximal Methods and Rounding Schemes (pdf, software)
  P. Ravikumar, A. Agarwal, M. Wainwright.
  Journal of Machine Learning Research (JMLR) 11, pp. 1043-1080, March 2010.
• High-dimensional Ising Model Selection using ℓ1-Regularized Logistic Regression (pdf, arXiv, software)
  P. Ravikumar, M. Wainwright, J. Lafferty.
  Annals of Statistics (Ann. Statist.) 38, pp. 1287-1319, 2010.

2009

• Clustering with Multiple Graphs (pdf, software)
  W. Tang, Z. Lu, I. Dhillon.
  In IEEE International Conference on Data Mining (ICDM), December 2009.
• Matrix Completion from Power-Law Distributed Samples (pdf, software)
  R. Meka, P. Jain, I. Dhillon.
  In Neural Information Processing Systems (NIPS), pp. 1258-1266, December 2009.
• A New Non-monotonic Algorithm for PET image reconstruction
  S. Sra, D. Kim, I. Dhillon, B. Schölkopf.
  In IEEE Medical Imaging Conference (MIC), October 2009.
• A Spatio-Temporal Approach to Collaborative Filtering (pdf, software)
  Z. Lu, D. Agarwal, I. Dhillon.
  In ACM Conference on Recommender Systems (RecSys), October 2009.
• A Scalable Framework for Discovering Coherent Co-clusters in Noisy Data (pdf, software)
  M. Deodhar, G. Gupta, J. Ghosh, H. Cho, I. Dhillon.
  In International Conference on Machine Learning (ICML), June 2009.
• Geometry-aware Metric Learning (pdf, software)
  Z. Lu, P. Jain, I. Dhillon.
  In International Conference on Machine Learning (ICML), June 2009.
• Convex Perturbations for Scalable Semidefinite Programming (pdf, software)
  B. Kulis, S. Sra, I. Dhillon.
  In International Conference on Artificial Intelligence and Statistics (AISTATS), April 2009.
• Low-Rank Kernel Learning with Bregman Matrix Divergences (pdf, software)
  B. Kulis, M. Sustik, I. Dhillon.
  Journal of Machine Learning Research (JMLR) 10, pp. 341-376, February 2009.
• Error-Correcting Tournaments (pdf, arXiv, software)
  A. Beygelzimer, J. Langford, P. Ravikumar.
  In International Conference on Algorithmic Learning Theory (ALT), 2009.
• Semi-Supervised Graph Clustering: A Kernel Approach (pdf, software)
  B. Kulis, S. Basu, I. Dhillon, R. Mooney.
  Machine Learning 74(1), pp. 1-22, January 2009.
• Sparse Additive Models (pdf, arXiv, software)
  P. Ravikumar, J. Lafferty, H. Liu, L. Wasserman.
  Journal of the Royal Statistical Society: Series B (Statistical Methodology) (JRSSB) 71(5), pp. 1009-1030, 2009.

2008

• Hunting for Coherent Co-clusters in High Dimensional and Noisy Datasets (pdf, software)
  M. Deodhar, H. Cho, G. Gupta, J. Ghosh, I. Dhillon.
  In IEEE International Conference on Data Mining (ICDM), December 2008.
• Model Selection in Gaussian Graphical Models: High-Dimensional Consistency of l1-Regularized MLE (pdf, software)
  P. Ravikumar, G. Raskutti, M. Wainwright, B. Yu.
  In Neural Information Processing Systems (NIPS), December 2008.
• Nonparametric sparse hierarchical models describe V1 fMRI responses to natural images (pdf, software)
  P. Ravikumar, V. Vu, B. Yu, T. Naselaris, K. Kay, J. Gallant.
  In Neural Information Processing Systems (NIPS), December 2008.
• Online Metric Learning and Fast Similarity Search (pdf, software)
  P. Jain, B. Kulis, I. Dhillon, K. Grauman.
  In Neural Information Processing Systems (NIPS), December 2008.
• Simultaneous Unsupervised Learning of Disparate Clusterings (pdf, software)
  P. Jain, R. Meka, I. Dhillon.
  Statistical Analysis and Data Mining 1(3), pp. 195-210, November 2008.
• Structured Metric Learning for High-Dimensional Problems (pdf, software)
  J. Davis, I. Dhillon.
  In ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), August 2008.
• Co-clustering of Human Cancer Microarrays using Minimum Sum-Squared Residue Co-clustering (pdf, software)
  H. Cho, I. Dhillon.
  IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) 5(3), pp. 385-400, July 2008.
• Message-passing for Graph-structured Linear Programs: Proximal Methods and Rounding Schemes (pdf, software)
  P. Ravikumar, A. Agarwal, M. Wainwright.
  In International Conference on Machine Learning (ICML), pp. 800-807, July 2008.
• Rank Minimization via Online Learning (pdf, software)
  R. Meka, P. Jain, C. Caramanis, I. Dhillon.
  In International Conference on Machine Learning (ICML), July 2008.
• Simultaneous Unsupervised Learning of Disparate Clusterings (pdf, software)
  P. Jain, R. Meka, I. Dhillon.
  In IEEE International Conference on Data Mining (ICDM), pp. 858-869, April 2008.
• The Metric Nearness Problem (pdf, software)
  J. Brickell, I. Dhillon, S. Sra, J. Tropp.
  SIAM Journal of Matrix Analysis and Applications (SIMAX) 30(1), pp. 375-396, April 2008.
• Fast Projection-Based Methods for the Least Squares Nonnegative Matrix Approximation Problem (pdf, software)
  D. Kim, S. Sra, I. Dhillon.
  Statistical Analysis and Data Mining 1(1), pp. 38-51, February 2008.
• Constructing Packings in Grassmannian Manifolds via Alternating Projections (pdf, software)
  I. Dhillon, R. Jr., T. Strohmer, J. Tropp.
  Experimental Mathematics 17(1), pp. 9-35, 2008.
• Single Index Convex Experts: Efficient Estimation via Adapted Bregman Losses (pdf, software)
  P. Ravikumar, M. Wainwright, B. Yu.
  Learning Workshop, Snowbird, 2008.

2007

• Matrix Nearness Problems with Bregman Divergences (pdf, software)
  I. Dhillon, J. Tropp.
  SIAM Journal of Matrix Analysis and Applications (SIMAX) 29(4), pp. 1120-1146, November 2007.
• Weighted Graph Cuts without Eigenvectors: A Multilevel Approach (pdf, software)
  I. Dhillon, Y. Guan, B. Kulis.
  IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI) 29(11), pp. 1944-1957, November 2007.
• On the Existence of Equiangular Tight Frames (pdf, software)
  M. Sustik, J. Tropp, I. Dhillon, R. Jr..
  Linear Algebra and its Applications 426(2), pp. 619-635, October 2007.
  (A previous version appears as UTCS Technical Report #TR-04-32, August 2004.)
• A Generalized Maximum Entropy Approach to Bregman Co-clustering and Matrix Approximations (pdf, software)
  A. Banerjee, I. Dhillon, J. Ghosh, S. Merugu, D. Modha.
  Journal of Machine Learning Research (JMLR) 8, pp. 1919-1986, August 2007.
• Information-Theoretic Metric Learning (pdf, software)
  J. Davis, B. Kulis, P. Jain, S. Sra, I. Dhillon.
  In International Conference on Machine Learning (ICML), June 2007.
• Fast Newton-type Methods for the Least Squares Nonnegative Matrix Approximation Problem (pdf, software)
  D. Kim, S. Sra, I. Dhillon.
  In SIAM International Conference on Data Mining (SDM), pp. 343-354, April 2007.
• Online Linear Regression using Burg Entropy (pdf, software)
  P. Jain, B. Kulis, I. Dhillon.
  University of Texas Computer Science Technical Report (UTCS Technical Report) TR-07-08, February 2007.

2006

• Differential Entropic Clustering of Multivariate Gaussians (pdf, software)
  J. Davis, I. Dhillon.
  In Neural Information Processing Systems (NIPS), pp. 337-344, December 2006.
• The Design and Implementation of the MRRR Algorithm (pdf, software)
  I. Dhillon, B. Parlett, C. Vömel.
  ACM Transactions on Mathematical Software 32(4), pp. 533-560, December 2006.
• Adaptive Website Design using Caching Algorithms (pdf, software)
  J. Brickell, I. Dhillon, D. Modha.
  ACM International Conference on Knowledge Discovery and Data Mining (KDD) (Workshop on Web Mining and Web Usage Analysis) (WebKDD), August 2006.
• Estimating the Global PageRank of Web Communities (pdf, software)
  J. Davis, I. Dhillon.
  In ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pp. 116-125, August 2006.
• Learning Low-Rank Kernel Matrices (pdf, software)
  B. Kulis, M. Sustik, I. Dhillon.
  In International Conference on Machine Learning (ICML), pp. 505-512, July 2006.
• Nonnegative Matrix Approximation: Algorithms and Applications (pdf, software)
  S. Sra, I. Dhillon.
  University of Texas Computer Science Technical Report (UTCS Technical Report) TR-06-27, June 2006.
• Computation of the Singular Value Decomposition (pdf, software)
  A. Cline, I. Dhillon.
  Handbook of Linear Algebra, pp. 45-1–45-13, January 2006.

2005

• Generalized Nonnegative Matrix Approximations with Bregman Divergences (pdf, software)
  I. Dhillon, S. Sra.
  In Neural Information Processing Systems (NIPS), pp. 283-290, December 2005.
• Clustering with Bregman Divergences (pdf, software)
  A. Banerjee, S. Merugu, I. Dhillon, J. Ghosh.
  Journal of Machine Learning Research (JMLR) 6, pp. 1705-1749, October 2005.
• Glued Matrices and the MRRR Algorithm (pdf, software)
  I. Dhillon, B. Parlett, C. Vömel.
  SIAM Journal on Scientific Computing 27(2), pp. 496-510, October 2005.
• A Parallel Eigensolver for Dense Symmetric Matrices based on Multiple Relatively Robust Representations (pdf, software)
  P. Bientinesi, I. Dhillon, R. Geijn.
  SIAM Journal on Scientific Computing 27(1), pp. 43-66, September 2005.
• Clustering on the Unit Hypersphere using von Mises-Fisher Distributions (pdf, software)
  A. Banerjee, I. Dhillon, J. Ghosh, S. Sra.
  Journal of Machine Learning Research (JMLR) 6, pp. 1345-1382, September 2005.
• A Fast Kernel-based Multilevel Algorithm for Graph Clustering (pdf, software)
  I. Dhillon, B. Kulis.
  In ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pp. 629-634, August 2005.
• Semi-supervised Graph Clustering: A Kernel Approach (pdf, software)
  B. Kulis, S. Basu, I. Dhillon, R. Mooney.
  In International Conference on Machine Learning (ICML), pp. 457-464, July 2005.
• Generalized Finite Algorithms for Constructing Hermitian Matrices with Prescribed Diagonal and Spectrum (pdf, software)
  I. Dhillon, R. Jr., M. Sustik, J. Tropp.
  SIAM Journal of Matrix Analysis and Applications (SIMAX) 27(1), pp. 61-71, June 2005.
• Clustering with Entropy-like k-means Algorithms (pdf, software)
  M. Teboulle, P. Berkhin, I. Dhillon, Y. Guan, J. Kogan.
  Grouping Multidimensional Data – Recent Advances in Clustering, pp. 127-160, January 2005.
• Designing Structured Tight Frames Via an Alternating Projection Method (pdf, software)
  J. Tropp, I. Dhillon, R. Jr., T. Strohmer.
  IEEE Transactions on Information Theory 51(1), pp. 188-209, January 2005.

2004

• Triangle Fixing Algorithms for the Metric Nearness Problem (pdf, software)
  I. Dhillon, S. Sra.
  In Neural Information Processing Systems (NIPS), pp. 361-368, December 2004.
• Finite-Step Algorithms for Constructing Optimal CDMA Signature Sequences (pdf, software)
  J. Tropp, I. Dhillon, R. Jr..
  IEEE Transactions on Information Theory 50(11), pp. 2916-2921, November 2004.
• Construction of Equiangular Signatures for Synchronous CDMA Systems (pdf, software)
  R. Jr., J. Tropp, I. Dhillon, T. Strohmer.
  IEEE International Symposium on Spread Spectrum Techniques and Applications,, August 2004.
• Kernel k-means, Spectral Clustering and Normalized Cuts (pdf, software)
  I. Dhillon, Y. Guan, B. Kulis.
  In ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pp. 551-556, August 2004.
  (A longer version appears as UTCS Technical Report #TR-04-25, June 30, 2004.)
• Multiple Representations to Compute Orthogonal Eigenvectors of Symmetric Tridiagonal Matrices (pdf, software)
  I. Dhillon, B. Parlett.
  Linear Algebra and its Applications 387, pp. 1-28, August 2004.
• Optimal CDMA Signatures: A Finite-Step Approach (pdf, software)
  J. Tropp, I. Dhillon, R. Jr..
  IEEE International Symposium on Spread Spectrum Techniques and Applications,, August 2004.
• A Generalized Maximum Entropy Approach to Bregman Co-clustering and Matrix Approximations (pdf, software)
  A. Banerjee, I. Dhillon, J. Ghosh, S. Merugu.
  In International Conference on Machine Learning (ICML), pp. 57-64, July 2004.
• An Information Theoretic Analysis of Maximum Likelihood Mixture Estimation for Exponential Families (pdf, software)
  A. Banerjee, I. Dhillon, J. Ghosh, S. Merugu.
  In International Conference on Machine Learning (ICML), July 2004.
• Clustering with Bregman Divergences (pdf, software)
  A. Banerjee, S. Merugu, I. Dhillon, J. Ghosh.
  In SIAM International Conference on Data Mining (SDM), pp. 234-245, April 2004.
• Minimum Sum-Squared Residue Co-clustering of Gene Expression Data (pdf, software)
  H. Cho, I. Dhillon, Y. Guan, S. Sra.
  In SIAM International Conference on Data Mining (SDM), pp. 114-125, April 2004.
• Orthogonal Eigenvectors and Relative Gaps (pdf, software)
  I. Dhillon, B. Parlett.
  SIAM Journal of Matrix Analysis and Applications (SIMAX) , pp. 858-899, March 2004.

2003

• CDMA Signature Sequences with Low Peak-To-Average Ratio via Alternating Projection (pdf, software)
  J. Tropp, I. Dhillon, R. Jr., T. Strohmer.
  In IEEE Asilomar Conference on Signals, Systems, and Computers, pp. 475-479, November 2003.
• Information Theoretic Clustering of Sparse Co-Occurrence Data (pdf, software)
  I. Dhillon, Y. Guan.
  In IEEE International Conference on Data Mining (ICDM), pp. 517-520, November 2003.
• Diametrical Clustering for identifying Anti-Correlated Gene Clusters (pdf, software)
  I. Dhillon, E. Marcotte, U. Roshan.
  Bioinformatics 19(13), pp. 1612-1619, September 2003.
• Generative Model-based Clustering of Directional Data (pdf, software)
  A. Banerjee, I. Dhillon, J. Ghosh, S. Sra.
  In ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pp. 19-28, August 2003.
• Information-Theoretic Co-clustering (pdf, software)
  I. Dhillon, S. Mallela, D. Modha.
  In ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pp. 89-98, August 2003.
• A Divisive Information-Theoretic Feature Clustering Algorithm for Text Classification (pdf, software)
  I. Dhillon, S. Mallela, R. Kumar.
  Journal of Machine Learning Research (JMLR) 3, pp. 1265-1287, March 2003.
• Feature Selection and Document Clustering (pdf, software)
  I. Dhillon, J. Kogan, M. Nicholas.
  A Comprehensive Survey of Text Mining, pp. 73-100, January 2003.
• Inner deflation of Symmetric, Tridiagonal Matrices (pdf, software)
  I. Dhillon, A. Malyshev.
  Linear Algebra and its Applications 358(1), pp. 139-144, January 2003.
• Modeling data using Directional Distributions (pdf, software)
  I. Dhillon, S. Sra.
  University of Texas Computer Science Technical Report (UTCS Technical Report) TR-03-06, January 2003.

2002

• Iterative Clustering of High Dimensional Text Data Augmented by Local Search (pdf, software)
  I. Dhillon, Y. Guan, J. Kogan.
  In IEEE International Conference on Data Mining (ICDM), pp. 131-138, December 2002.
• Class Visualization of High-Dimensional Data with Applications (pdf, software)
  I. Dhillon, D. Modha, W. Spangler.
  Computational Statistics & Data Analysis (Special issue on Matrix Computations & Statistics) 4(1), pp. 59-90, November 2002.
• Diametrical Clustering for identifying Anti-Correlated Gene Clusters (pdf, software)
  I. Dhillon, E. Marcotte, U. Roshan.
  University of Texas Computer Science Technical Report (UTCS Technical Report) TR-02-49, September 2002.
• Enhanced Word Clustering for Hierarchical Text Classification (pdf, software)
  I. Dhillon, S. Mallela, R. Kumar.
  In ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), July 2002.
• Refining Clusters in High-dimensional Text Data (pdf, software)
  I. Dhillon, Y. Guan, J. Kogan.
  In SIAM International Conference on Data Mining (SDM), April 2002.

2001

• Co-clustering Documents and Words Using Bipartite Spectral Graph Partitioning (pdf, software)
  I. Dhillon.
  In ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), August 2001.
• Concept Decompositions for Large Sparse Text Data using Clustering (pdf, software)
  I. Dhillon, D. Modha.
  Machine Learning , January 2001.
• Efficient Clustering of Very Large Document Collections (pdf, software)
  I. Dhillon, Y. Guan, J. Fan.
  Data Mining for Scientific and Engineering Applications, pp. 357-381, 2001.
  (Invited chapter)

2000

• Relatively Robust Representations for Symmetric Tridiagonals (pdf, software)
  B. Parlett, I. Dhillon.
  Linear Algebra and its Applications 309, pp. 121-151, November 2000.

1999

• A Data Clustering Algorithm on Distributed Memory Multiprocessors (pdf, software)
  I. Dhillon, D. Modha.
  In ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), August 1999.
  (Also appears as IBM Research Report RJ 10134.)
• Concept Decompositions for Large Sparse Text Data using Clustering (pdf, software)
  I. Dhillon, D. Modha.
  IBM Research Report RJ 10147, July 1999.

1998

• Current Inverse Iteration Software can Fail (pdf, software)
  I. Dhillon.
  BIT Numerical Mathematics 38(4), pp. 685-704, December 1998.
• Reliable computation of the Condition Number of a Tridiagonal Matrix in O(n) Time (pdf, software)
  I. Dhillon.
  SIAM Journal of Matrix Analysis and Applications (SIMAX) 19(3), pp. 776-796, July 1998.
• Visualizing Class Structure of Multidimensional Data (pdf, software)
  I. Dhillon, D. Modha, W. Spangler.
  Symposium on the Interface: Computing Science and Statistics, pp. 488-493, May 1998.

1997

• Practical Experience in the Numerical Dangers of Heterogeneous Computing (pdf, software)
  L. Blackford, A. Cleary, J. Demmel, I. Dhillon, J. Dongarra, S. Hammarling, A. Petitet, H. Ren, K. Stanley, R. Whaley.
  ACM Transactions on Mathematical Software 23(2), pp. 133-147, June 1997.
• A New O(N^2) Algorithm for the Symmetric Tridiagonal Eigenvalue/Eigenvector Problem (pdf, software)
  I. Dhillon.
  Ph.D. Thesis, May 1997.
  (Also appears as UCB Tech. Report No. UCB//CSD-97-971)
• Application of a New Algorithm for the Symmetric Eigenproblem to Computational Quantum Chemistry (pdf, software)
  I. Dhillon, G. Fann, B. Parlett.
  In SIAM Conference on Parallel Processing for Scientific Computing, March 1997.
• ScaLAPACK: A Linear Algebra Library for Message-Passing Computers (pdf, software)
  L. Blackford, J. Choi, A. Cleary, E. D’Azevedo, J. Demmel, I. Dhillon, J. Dongarra, S. Hammarling, G. Henry, A. Petitet, K. Stanley, D. Walker, R. Whaley.
  In SIAM Conference on Parallel Processing for Scientific Computing, March 1997.
• Fernando’s Solution to Wilkinson’s Problem: An Application of Double Factorization (pdf, software)
  B. Parlett, I. Dhillon.
  Linear Algebra and its Applications, pp. 247-279, 1997.
• ScaLAPACK Users’ Guide (pdf, software)
  L. Blackford, J. Choi, A. Cleary, J. Demmel, I. Dhillon, J. Dongarra, S. Hammarling, G. Henry, A. Petitet, K. Stanley, D. Walker, R. Whaley.
  ScaLAPACK Users’ Guide, 1997.

1996

• ScaLAPACK: A Portable Linear Algebra Library for Distributed Memory Computers – Design Issues and Performance (pdf, software)
  J. Choi, J. Demmel, I. Dhillon, J. Dongarra, S. Ostrouchov, A. Petitet, K. Stanley, D. Walker, R. Whaley.
  Computer Physics Communications 97, pp. 1-15, August 1996.
• ScaLAPACK: A Portable Linear Algebra Library for Distributed Memory Computers – Design Issues and Performance (pdf, software)
  L. Blackford, J. Choi, A. Cleary, J. Demmel, I. Dhillon, J. Dongarra, S. Hammarling, G. Henry, A. Petitet, K. Stanley, D. Walker, R. Whaley.
  In Supercomputing (SC), 1996.

1995

• On the Correctness of Some Bisection-like Parallel Algorithms in Floating Point Arithmetic (pdf, software)
  J. Demmel, I. Dhillon, H. Ren.
  Electronic Transactions of Numerical Analysis (ETNA), December 1995.
• Installation Guide for ScaLAPACK (pdf, software)
  J. Choi, J. Demmel, I. Dhillon, J. Dongarra, S. Ostrouchov, A. Petitet, K. Stanley, D. Walker, R. Whaley.
  University of Tennessee Computer Science Technical Report (UT-CS-95-280) UT-CS-95-280, March 1995.
  (updated August 31, 2001 (version 1.7) — also available as LAPACK Working Note 93)

1994

• Efficient Computation of the Singular Value Decomposition with Applications to Least Squares Problems (pdf, software)
  M. Gu, J. Demmel, I. Dhillon.
  Technical Report LBL-36201, October 1994.

1991

• An Overview of the Compilation Process for a New Parallel Architecture (pdf, software)
  I. Dhillon, N. Karmarkar, K. Ramakrishnan.
  Supercomputing Symposium, pp. 471-486, June 1991.

1990

• Performance Analysis of a Proposed Parallel Architecture on Matrix Vector Multiply Like Routines (pdf, software)
  I. Dhillon, N. Karmarkar, K. Ramakrishnan.
  Technical Memorandum 11216-901004-13TM, 1990.