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All publications by Inderjit S. Dhillon
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Matrix Completion with Noisy Side Information
Kai-yang Chiang, Cho-jui Hsieh and Inderjit S. Dhillon
Advances in Neural Information Processing Systems 28, 2015


Collaborative Filtering with Graph Information: Consistency and Scalable Methods
Nikhil Rao, Hsiang-fu Yu, Pradeep K. Ravikumar and Inderjit S. Dhillon
Advances in Neural Information Processing Systems 28, 2015


Sparse Linear Programming via Primal and Dual Augmented Coordinate Descent
Ian E. Yen, Kai Zhong, Cho-jui Hsieh, Pradeep K. Ravikumar and Inderjit S. Dhillon
Advances in Neural Information Processing Systems 28, 2015


Consistent Multilabel Classification
Oluwasanmi O. Koyejo, Nagarajan Natarajan, Pradeep K. Ravikumar and Inderjit S. Dhillon
Advances in Neural Information Processing Systems 28, 2015


Fixed-Length Poisson MRF: Adding Dependencies to the Multinomial
David I. Inouye, Pradeep K. Ravikumar and Inderjit S. Dhillon
Advances in Neural Information Processing Systems 28, 2015


QUIC \& DIRTY: A Quadratic Approximation Approach for Dirty Statistical Models
Cho-jui Hsieh, Inderjit S. Dhillon, Pradeep K. Ravikumar, Stephen Becker and Peder A. Olsen
Advances in Neural Information Processing Systems 27, 2014


Multi-Scale Spectral Decomposition of Massive Graphs
Si Si, Donghyuk Shin, Inderjit S. Dhillon and Beresford N. Parlett
Advances in Neural Information Processing Systems 27, 2014


Fast Prediction for Large-Scale Kernel Machines
Cho-jui Hsieh, Si Si and Inderjit S. Dhillon
Advances in Neural Information Processing Systems 27, 2014


Sparse Random Feature Algorithm as Coordinate Descent in Hilbert Space
En-hsu Yen, Ting-wei Lin, Shou-de Lin, Pradeep K. Ravikumar and Inderjit S. Dhillon
Advances in Neural Information Processing Systems 27, 2014


Consistent Binary Classification with Generalized Performance Metrics
Oluwasanmi O. Koyejo, Nagarajan Natarajan, Pradeep K. Ravikumar and Inderjit S. Dhillon
Advances in Neural Information Processing Systems 27, 2014


Proximal Quasi-Newton for Computationally Intensive L1-regularized M-estimators
Kai Zhong, En-hsu Yen, Inderjit S. Dhillon and Pradeep K. Ravikumar
Advances in Neural Information Processing Systems 27, 2014


Capturing Semantically Meaningful Word Dependencies with an Admixture of Poisson MRFs
David Inouye, Pradeep K. Ravikumar and Inderjit S. Dhillon
Advances in Neural Information Processing Systems 27, 2014


Constant Nullspace Strong Convexity and Fast Convergence of Proximal Methods under High-Dimensional Settings
En-hsu Yen, Cho-jui Hsieh, Pradeep K. Ravikumar and Inderjit S. Dhillon
Advances in Neural Information Processing Systems 27, 2014


A Divide-and-Conquer Method for Sparse Inverse Covariance Estimation
Cho-jui Hsieh, Arindam Banerjee, Inderjit S. Dhillon and Pradeep K. Ravikumar
Advances in Neural Information Processing Systems 25, 2012


Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation
Cho-jui Hsieh, Inderjit S. Dhillon, Pradeep K. Ravikumar and Mátyás A. Sustik
Advances in Neural Information Processing Systems 24, 2011


Nearest Neighbor based Greedy Coordinate Descent
Inderjit S. Dhillon, Pradeep K. Ravikumar and Ambuj Tewari
Advances in Neural Information Processing Systems 24, 2011


Orthogonal Matching Pursuit with Replacement
Prateek Jain, Ambuj Tewari and Inderjit S. Dhillon
Advances in Neural Information Processing Systems 24, 2011


Greedy Algorithms for Structurally Constrained High Dimensional Problems
Ambuj Tewari, Pradeep K. Ravikumar and Inderjit S. Dhillon
Advances in Neural Information Processing Systems 24, 2011


A scalable trust-region algorithm with application to mixed-norm regression
Dongmin Kim, Suvrit Sra and Inderjit S. Dhillon
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Guaranteed Rank Minimization via Singular Value Projection
Prateek Jain, Raghu Meka and Inderjit S. Dhillon
Advances in Neural Information Processing Systems 23, 2010


Inductive Regularized Learning of Kernel Functions
Prateek Jain, Brian Kulis and Inderjit S. Dhillon
Advances in Neural Information Processing Systems 23, 2010


Low-Rank Kernel Learning with Bregman Matrix Divergences
Brian Kulis, Mátyás A. Sustik and Inderjit S. Dhillon
Journal of Machine Learning Research, 2009


Geometry-aware metric learning
Zhengdong Lu, Prateek Jain and Inderjit S. Dhillon
Proceedings of the 26th International Conference on Machine Learning (ICML-09), 2009


A scalable framework for discovering coherent co-clusters in noisy data
Meghana Deodhar, Gunjan Gupta, Joydeep Ghosh, Hyuk Cho and Inderjit S. Dhillon
Proceedings of the 26th International Conference on Machine Learning (ICML-09), 2009


Matrix Completion from Power-Law Distributed Samples
Raghu Meka, Prateek Jain and Inderjit S. Dhillon
Advances in Neural Information Processing Systems 22, 2009


Convex Perturbations for Scalable Semidefinite Programming
Brian Kulis, Suvrit Sra and Inderjit S. Dhillon
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics (AISTATS-09), 2009


Rank minimization via online learning
Raghu Meka, Prateek Jain, Constantine Caramanis and Inderjit S. Dhillon
Proceedings of the 25th International Conference on Machine Learning (ICML-08), 2008


Online Metric Learning and Fast Similarity Search
Prateek Jain, Brian Kulis, Inderjit S. Dhillon and Kristen Grauman
Advances in Neural Information Processing Systems 21, 2008


Information-theoretic metric learning
Jason V. Davis, Brian Kulis, Prateek Jain, Suvrit Sra and Inderjit S. Dhillon
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


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


Learning low-rank kernel matrices
Brian Kulis, Mátyás A. Sustik and Inderjit S. Dhillon
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006


Differential Entropic Clustering of Multivariate Gaussians
Jason V. Davis and Inderjit S. Dhillon
Advances in Neural Information Processing Systems 19, 2006


Semi-supervised graph clustering: a kernel approach
Brian Kulis, Sugato Basu, Inderjit S. Dhillon and Raymond J. Mooney
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Generalized Nonnegative Matrix Approximations with Bregman Divergences
Suvrit Sra and Inderjit S. Dhillon
Advances in Neural Information Processing Systems 18, 2005


Clustering with Bregman Divergences
Arindam Banerjee, Srujana Merugu, Inderjit S. Dhillon and Joydeep Ghosh
Journal of Machine Learning Research, 2005


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


An information theoretic analysis of maximum likelihood mixture estimation for exponential families
Arindam Banerjee, Inderjit S. Dhillon, Joydeep Ghosh and Srujana Merugu
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Triangle Fixing Algorithms for the Metric Nearness Problem
Suvrit Sra, Joel Tropp and Inderjit S. Dhillon
Advances in Neural Information Processing Systems 17, 2004


A Divisive Information-Theoretic Feature Clustering Algorithm for Text Classification
Inderjit S. Dhillon, Subramanyam Mallela and Rahul Kumar
Journal of Machine Learning Research, 2003