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

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

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

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

Application of a New Algorithm for the Symmetric Eigenproblem to Computational Quantum Chemistry. - Inderjit S. Dhillon; George Fann; Beresford N. Parlett (PP, 1997)

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

Reliable Computation of the Condition Number of a Tridiagonal Matrix in O(n) Time. - Inderjit S. Dhillon (SIAM J. Matrix Anal. Appl., 1998)

A Data-Clustering Algorithm on Distributed Memory Multiprocessors. - Inderjit S. Dhillon; Dharmendra S. Modha (Large-Scale Parallel Data Mining, 1999)

Co-clustering documents and words using bipartite spectral graph partitioning. - Inderjit S. Dhillon (KDD, 2001)

Concept Decompositions for Large Sparse Text Data Using Clustering. - Inderjit S. Dhillon; Dharmendra S. Modha (Mach. Learn., 2001)

Iterative Clustering of High Dimensional Text Data Augmented by Local Search. - Inderjit S. Dhillon; Yuqiang Guan; Jacob Kogan (ICDM, 2002)

Enhanced word clustering for hierarchical text classification. - Inderjit S. Dhillon; Subramanyam Mallela; Rahul Kumar (KDD, 2002)

Class visualization of high-dimensional data with applications. - Inderjit S. Dhillon; Dharmendra S. Modha; W. Scott Spangler (Comput. Stat. Data Anal., 2002)

Information Theoretic Clustering of Sparse Co-Occurrence Data. - Inderjit S. Dhillon; Yuqiang Guan (ICDM, 2003)

Generative model-based clustering of directional data. - Arindam Banerjee 001; Inderjit S. Dhillon; Joydeep Ghosh; Suvrit Sra (KDD, 2003)

Information-theoretic co-clustering. - Inderjit S. Dhillon; Subramanyam Mallela; Dharmendra S. Modha (KDD, 2003)

Diametrical clustering for identifying anti-correlated gene clusters. - Inderjit S. Dhillon; Edward M. Marcotte; Usman Roshan (Bioinform., 2003)

A Divisive Information-Theoretic Feature Clustering Algorithm for Text Classification. - Inderjit S. Dhillon; Subramanyam Mallela; Rahul Kumar (J. Mach. Learn. Res., 2003)

Orthogonal Eigenvectors and Relative Gaps. - Inderjit S. Dhillon; Beresford N. Parlett (SIAM J. Matrix Anal. Appl., 2003)

An information theoretic analysis of maximum likelihood mixture estimation for exponential families. - Arindam Banerjee 001; Inderjit S. Dhillon; Joydeep Ghosh; Srujana Merugu (ICML, 2004)

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

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

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

Finite-Step Algorithms for Constructing Optimal CDMA Signature Sequences. - Joel A. Tropp; Inderjit S. Dhillon; Robert W. Heath Jr. (IEEE Trans. Inf. Theory, 2004)

A fast kernel-based multilevel algorithm for graph clustering. - Inderjit S. Dhillon; Yuqiang Guan; Brian Kulis (KDD, 2005)

Generalized Nonnegative Matrix Approximations with Bregman Divergences. - Inderjit S. Dhillon; Suvrit Sra (NIPS, 2005)

Clustering on the Unit Hypersphere using von Mises-Fisher Distributions. - Arindam Banerjee 001; Inderjit S. Dhillon; Joydeep Ghosh; Suvrit Sra (J. Mach. Learn. Res., 2005)

Clustering with Bregman Divergences. - Arindam Banerjee 001; Srujana Merugu; Inderjit S. Dhillon; Joydeep Ghosh (J. Mach. Learn. Res., 2005)

Generalized Finite Algorithms for Constructing Hermitian Matrices with Prescribed Diagonal and Spectrum. - Inderjit S. Dhillon; Robert W. Heath Jr.; Mátyás A. Sustik; Joel A. Tropp (SIAM J. Matrix Anal. Appl., 2005)

A Parallel Eigensolver for Dense Symmetric Matrices Based on Multiple Relatively Robust Representations. - Paolo Bientinesi; Inderjit S. Dhillon; Robert A. van de Geijn (SIAM J. Sci. Comput., 2005)

Glued Matrices and the MRRR Algorithm. - Inderjit S. Dhillon; Beresford N. Parlett; Christof Vömel (SIAM J. Sci. Comput., 2005)

Designing structured tight frames via an alternating projection method. - Joel A. Tropp; Inderjit S. Dhillon; Robert W. Heath Jr.; Thomas Strohmer (IEEE Trans. Inf. Theory, 2005)

Clustering with Entropy-Like k-Means Algorithms. - Marc Teboulle; Pavel Berkhin; Inderjit S. Dhillon; Yuqiang Guan; Jacob Kogan (Grouping Multidimensional Data, 2006)

Learning low-rank kernel matrices. - Brian Kulis; Mátyás A. Sustik; Inderjit S. Dhillon (ICML, 2006)

Adaptive Website Design Using Caching Algorithms. - Justin Brickell; Inderjit S. Dhillon; Dharmendra S. Modha (WEBKDD, 2006)

Estimating the global pagerank of web communities. - Jason V. Davis; Inderjit S. Dhillon (KDD, 2006)

Differential Entropic Clustering of Multivariate Gaussians. - Jason V. Davis; Inderjit S. Dhillon (NIPS, 2006)

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

Information-theoretic metric learning. - Jason V. Davis; Brian Kulis; Prateek Jain 002; Suvrit Sra; Inderjit S. Dhillon (ICML, 2007)

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

A Generalized Maximum Entropy Approach to Bregman Co-clustering and Matrix Approximation. - Arindam Banerjee 001; Inderjit S. Dhillon; Joydeep Ghosh; Srujana Merugu; Dharmendra S. Modha (J. Mach. Learn. Res., 2007)

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

Matrix Nearness Problems with Bregman Divergences. - Inderjit S. Dhillon; Joel A. Tropp (SIAM J. Matrix Anal. Appl., 2007)

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

Rank minimization via online learning. - Raghu Meka; Prateek Jain 002; Constantine Caramanis; Inderjit S. Dhillon (ICML, 2008)

Structured metric learning for high dimensional problems. - Jason V. Davis; Inderjit S. Dhillon (KDD, 2008)

Online Metric Learning and Fast Similarity Search. - Prateek Jain 002; Brian Kulis; Inderjit S. Dhillon; Kristen Grauman (NIPS, 2008)

Constructing Packings in Grassmannian Manifolds via Alternating Projection. - Inderjit S. Dhillon; Robert W. Heath Jr.; Thomas Strohmer; Joel A. Tropp (Exp. Math., 2008)

Simultaneous Unsupervised Learning of Disparate Clusterings. - Prateek Jain 002; Raghu Meka; Inderjit S. Dhillon (Stat. Anal. Data Min., 2008)

Fast Projection-Based Methods for the Least Squares Nonnegative Matrix Approximation Problem. - Dongmin Kim; Suvrit Sra; Inderjit S. Dhillon (Stat. Anal. Data Min., 2008)

The Metric Nearness Problem. - Justin Brickell; Inderjit S. Dhillon; Suvrit Sra; Joel A. Tropp (SIAM J. Matrix Anal. Appl., 2008)

Coclustering of Human Cancer Microarrays Using Minimum Sum-Squared Residue Coclustering. - Hyuk Cho; Inderjit S. Dhillon (IEEE ACM Trans. Comput. Biol. Bioinform., 2008)

Clustering with Multiple Graphs. - Wei Tang; Zhengdong Lu; Inderjit S. Dhillon (ICDM, 2009)

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

Geometry-aware metric learning. - Zhengdong Lu; Prateek Jain 002; Inderjit S. Dhillon (ICML, 2009)

Matrix Completion from Power-Law Distributed Samples. - Raghu Meka; Prateek Jain 002; Inderjit S. Dhillon (NIPS, 2009)

A spatio-temporal approach to collaborative filtering. - Zhengdong Lu; Deepak Agarwal; Inderjit S. Dhillon (RecSys, 2009)

Low-Rank Kernel Learning with Bregman Matrix Divergences. - Brian Kulis; Mátyás A. Sustik; Inderjit S. Dhillon (J. Mach. Learn. Res., 2009)

Convex Perturbations for Scalable Semidefinite Programming. - Brian Kulis; Suvrit Sra; Inderjit S. Dhillon (AISTATS, 2009)

Semi-supervised graph clustering: a kernel approach. - Brian Kulis; Sugato Basu; Inderjit S. Dhillon; Raymond J. Mooney (Mach. Learn., 2009)

Knowledge Discovery: Clustering. - Pavel Berkhin; Inderjit S. Dhillon (Encyclopedia of Complexity and Systems Science, 2009)

Supervised Link Prediction Using Multiple Sources. - Zhengdong Lu; Berkant Savas; Wei Tang; Inderjit S. Dhillon (ICDM, 2010)

A scalable trust-region algorithm with application to mixed-norm regression. - Dongmin Kim; Suvrit Sra; Inderjit S. Dhillon (ICML, 2010)

Inductive Regularized Learning of Kernel Functions. - Prateek Jain 002; Brian Kulis; Inderjit S. Dhillon (NIPS, 2010)

Guaranteed Rank Minimization via Singular Value Projection. - Prateek Jain 002; Raghu Meka; Inderjit S. Dhillon (NIPS, 2010)

Affiliation recommendation using auxiliary networks. - Vishvas Vasuki; Nagarajan Natarajan; Zhengdong Lu; Inderjit S. Dhillon (RecSys, 2010)

Tackling Box-Constrained Optimization via a New Projected Quasi-Newton Approach. - Dongmin Kim; Suvrit Sra; Inderjit S. Dhillon (SIAM J. Sci. Comput., 2010)

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

Fast coordinate descent methods with variable selection for non-negative matrix factorization. - Cho-Jui Hsieh; Inderjit S. Dhillon (KDD, 2011)

Nearest Neighbor based Greedy Coordinate Descent. - Inderjit S. Dhillon; Pradeep Ravikumar; Ambuj Tewari (NIPS, 2011)

Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation. - Cho-Jui Hsieh; Mátyás A. Sustik; Inderjit S. Dhillon; Pradeep Ravikumar (NIPS, 2011)

Orthogonal Matching Pursuit with Replacement. - Prateek Jain 002; Ambuj Tewari; Inderjit S. Dhillon (NIPS, 2011)

Greedy Algorithms for Structurally Constrained High Dimensional Problems. - Ambuj Tewari; Pradeep Ravikumar; Inderjit S. Dhillon (NIPS, 2011)

Clustered low rank approximation of graphs in information science applications. - Berkant Savas; Inderjit S. Dhillon (SDM, 2011)

Preface. - Alexandre d'Aspremont; Francis R. Bach; Inderjit S. Dhillon; Bin Yu 001 (Math. Program., 2011)

Scalable Affiliation Recommendation using Auxiliary Networks. - Vishvas Vasuki; Nagarajan Natarajan; Zhengdong Lu; Berkant Savas; Inderjit S. Dhillon (ACM Trans. Intell. Syst. Technol., 2011)

Scalable clustering of signed networks using balance normalized cut. - Kai-Yang Chiang; Joyce Jiyoung Whang; Inderjit S. Dhillon (CIKM, 2012)

Multi-scale link prediction. - Donghyuk Shin; Si Si; Inderjit S. Dhillon (CIKM, 2012)

Scalable and Memory-Efficient Clustering of Large-Scale Social Networks. - Joyce Jiyoung Whang; Xin Sui; Inderjit S. Dhillon (ICDM, 2012)

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

Low rank modeling of signed networks. - Cho-Jui Hsieh; Kai-Yang Chiang; Inderjit S. Dhillon (KDD, 2012)

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

A Divide-and-Conquer Method for Sparse Inverse Covariance Estimation. - Cho-Jui Hsieh; Inderjit S. Dhillon; Pradeep Ravikumar; Arindam Banerjee 001 (NIPS, 2012)

Clustered embedding of massive social networks. - Han Hee Song; Berkant Savas; Tae Won Cho; Vacha Dave; Zhengdong Lu; Inderjit S. Dhillon; Yin Zhang 001; Lili Qiu (SIGMETRICS, 2012)

Metric and Kernel Learning Using a Linear Transformation. - Prateek Jain 002; Brian Kulis; Jason V. Davis; Inderjit S. Dhillon (J. Mach. Learn. Res., 2012)

On a Zero-Finding Problem Involving the Matrix Exponential. - Mátyás A. Sustik; Inderjit S. Dhillon (SIAM J. Matrix Anal. Appl., 2012)

Overlapping community detection using seed set expansion. - Joyce Jiyoung Whang; David F. Gleich; Inderjit S. Dhillon (CIKM, 2013)

Scalable Network Analysis. - Inderjit S. Dhillon (COMAD, 2013)

Stochastic Blockmodel with Cluster Overlap, Relevance Selection, and Similarity-Based Smoothing. - Joyce Jiyoung Whang; Piyush Rai; Inderjit S. Dhillon (ICDM, 2013)

BIG & QUIC: Sparse Inverse Covariance Estimation for a Million Variables. - Cho-Jui Hsieh; Mátyás A. Sustik; Inderjit S. Dhillon; Pradeep Ravikumar; Russell A. Poldrack (NIPS, 2013)

Learning with Noisy Labels. - Nagarajan Natarajan; Inderjit S. Dhillon; Pradeep Ravikumar; Ambuj Tewari (NIPS, 2013)

Large Scale Distributed Sparse Precision Estimation. - Huahua Wang; Arindam Banerjee 001; Cho-Jui Hsieh; Pradeep Ravikumar; Inderjit S. Dhillon (NIPS, 2013)

Which app will you use next?: collaborative filtering with interactional context. - Nagarajan Natarajan; Donghyuk Shin; Inderjit S. Dhillon (RecSys, 2013)

Provable Inductive Matrix Completion. - Prateek Jain 002; Inderjit S. Dhillon (CoRR, 2013)

Large-scale Multi-label Learning with Missing Labels. - Hsiang-Fu Yu; Prateek Jain 002; Inderjit S. Dhillon (CoRR, 2013)

NOMAD: Non-locking, stOchastic Multi-machine algorithm for Asynchronous and Decentralized matrix completion. - Hyokun Yun; Hsiang-Fu Yu; Cho-Jui Hsieh; S. V. N. Vishwanathan; Inderjit S. Dhillon (CoRR, 2013)

A non-monotonic method for large-scale non-negative least squares. - Dongmin Kim; Suvrit Sra; Inderjit S. Dhillon (Optim. Methods Softw., 2013)

A Divide-and-Conquer Solver for Kernel Support Vector Machines. - Cho-Jui Hsieh; Si Si; Inderjit S. Dhillon (ICML, 2014)

Admixture of Poisson MRFs: A Topic Model with Word Dependencies. - David I. Inouye; Pradeep Ravikumar; Inderjit S. Dhillon (ICML, 2014)

Large-scale Multi-label Learning with Missing Labels. - Hsiang-Fu Yu; Prateek Jain 002; Purushottam Kar; Inderjit S. Dhillon (ICML, 2014)

QUIC & DIRTY: A Quadratic Approximation Approach for Dirty Statistical Models. - Cho-Jui Hsieh; Inderjit S. Dhillon; Pradeep Ravikumar; Stephen Becker; Peder A. Olsen (NIPS, 2014)

Fast Prediction for Large-Scale Kernel Machines. - Cho-Jui Hsieh; Si Si; Inderjit S. Dhillon (NIPS, 2014)

Capturing Semantically Meaningful Word Dependencies with an Admixture of Poisson MRFs. - David I. Inouye; Pradeep Ravikumar; Inderjit S. Dhillon (NIPS, 2014)

Consistent Binary Classification with Generalized Performance Metrics. - Oluwasanmi Koyejo; Nagarajan Natarajan; Pradeep Ravikumar; Inderjit S. Dhillon (NIPS, 2014)

Multi-Scale Spectral Decomposition of Massive Graphs. - Si Si; Donghyuk Shin; Inderjit S. Dhillon; Beresford N. Parlett (NIPS, 2014)

Constant Nullspace Strong Convexity and Fast Convergence of Proximal Methods under High-Dimensional Settings. - Ian En-Hsu Yen; Cho-Jui Hsieh; Pradeep Ravikumar; Inderjit S. Dhillon (NIPS, 2014)

Sparse Random Feature Algorithm as Coordinate Descent in Hilbert Space. - Ian En-Hsu Yen; Ting-Wei Lin; Shou-De Lin; Pradeep Ravikumar; Inderjit S. Dhillon (NIPS, 2014)

Proximal Quasi-Newton for Computationally Intensive L1-regularized M-estimators. - Kai Zhong; Ian En-Hsu Yen; Inderjit S. Dhillon; Pradeep Ravikumar (NIPS, 2014)

Inductive matrix completion for predicting gene-disease associations. - Nagarajan Natarajan; Inderjit S. Dhillon (Bioinform., 2014)

Prediction and clustering in signed networks: a local to global perspective. - Kai-Yang Chiang; Cho-Jui Hsieh; Nagarajan Natarajan; Inderjit S. Dhillon; Ambuj Tewari (J. Mach. Learn. Res., 2014)

QUIC: quadratic approximation for sparse inverse covariance estimation. - Cho-Jui Hsieh; Mátyás A. Sustik; Inderjit S. Dhillon; Pradeep Ravikumar (J. Mach. Learn. Res., 2014)

Parallel matrix factorization for recommender systems. - Hsiang-Fu Yu; Cho-Jui Hsieh; Si Si; Inderjit S. Dhillon (Knowl. Inf. Syst., 2014)

NOMAD: Nonlocking, stOchastic Multi-machine algorithm for Asynchronous and Decentralized matrix completion. - Hyokun Yun; Hsiang-Fu Yu; Cho-Jui Hsieh; S. V. N. Vishwanathan; Inderjit S. Dhillon (Proc. VLDB Endow., 2014)

Efficient Matrix Sensing Using Rank-1 Gaussian Measurements. - Kai Zhong; Prateek Jain 002; Inderjit S. Dhillon (ALT, 2015)

PU matrix completion with graph information. - Nagarajan Natarajan; Nikhil Rao 001; Inderjit S. Dhillon (CAMSAP, 2015)

Tumblr Blog Recommendation with Boosted Inductive Matrix Completion. - Donghyuk Shin; Suleyman Cetintas; Kuang-Chih Lee; Inderjit S. Dhillon (CIKM, 2015)

Scalable Data-Driven PageRank: Algorithms, System Issues, and Lessons Learned. - Joyce Jiyoung Whang; Andrew Lenharth; Inderjit S. Dhillon; Keshav Pingali (Euro-Par, 2015)

Clustering to forecast sparse time-series data. - Abhay Jha; Shubhankar Ray; Brian Seaman; Inderjit S. Dhillon (ICDE, 2015)

PU Learning for Matrix Completion. - Cho-Jui Hsieh; Nagarajan Natarajan; Inderjit S. Dhillon (ICML, 2015)

PASSCoDe: Parallel ASynchronous Stochastic dual Co-ordinate Descent. - Cho-Jui Hsieh; Hsiang-Fu Yu; Inderjit S. Dhillon (ICML, 2015)

Preference Completion: Large-scale Collaborative Ranking from Pairwise Comparisons. - Dohyung Park; Joe Neeman; Jin Zhang; Sujay Sanghavi; Inderjit S. Dhillon (ICML, 2015)

A Convex Exemplar-based Approach to MAD-Bayes Dirichlet Process Mixture Models. - Ian En-Hsu Yen; Xin Lin; Kai Zhong; Pradeep Ravikumar; Inderjit S. Dhillon (ICML, 2015)

Non-exhaustive, Overlapping Clustering via Low-Rank Semidefinite Programming. - Yangyang Hou; Joyce Jiyoung Whang; David F. Gleich; Inderjit S. Dhillon (KDD, 2015)

Matrix Completion with Noisy Side Information. - Kai-Yang Chiang; Cho-Jui Hsieh; Inderjit S. Dhillon (NIPS, 2015)

Fixed-Length Poisson MRF: Adding Dependencies to the Multinomial. - David I. Inouye; Pradeep Ravikumar; Inderjit S. Dhillon (NIPS, 2015)

Consistent Multilabel Classification. - Oluwasanmi Koyejo; Nagarajan Natarajan; Pradeep Ravikumar; Inderjit S. Dhillon (NIPS, 2015)

Collaborative Filtering with Graph Information: Consistency and Scalable Methods. - Nikhil Rao 001; Hsiang-Fu Yu; Pradeep Ravikumar; Inderjit S. Dhillon (NIPS, 2015)

Sparse Linear Programming via Primal and Dual Augmented Coordinate Descent. - Ian En-Hsu Yen; Kai Zhong; Cho-Jui Hsieh; Pradeep Ravikumar; Inderjit S. Dhillon (NIPS, 2015)

Non-exhaustive, Overlapping k-means. - Joyce Jiyoung Whang; Inderjit S. Dhillon; David F. Gleich (SDM, 2015)

A Scalable Asynchronous Distributed Algorithm for Topic Modeling. - Hsiang-Fu Yu; Cho-Jui Hsieh; Hyokun Yun; S. V. N. Vishwanathan; Inderjit S. Dhillon (WWW, 2015)

Optimal Decision-Theoretic Classification Using Non-Decomposable Performance Metrics. - Nagarajan Natarajan; Oluwasanmi Koyejo; Pradeep Ravikumar; Inderjit S. Dhillon (CoRR, 2015)

Coordinate Descent Methods for Symmetric Nonnegative Matrix Factorization. - Arnaud Vandaele; Nicolas Gillis; Qi Lei; Kai Zhong; Inderjit S. Dhillon (CoRR, 2015)

Temporal Regularized Matrix Factorization. - Hsiang-Fu Yu; Nikhil Rao 001; Inderjit S. Dhillon (CoRR, 2015)

Robust Principal Component Analysis with Side Information. - Kai-Yang Chiang; Cho-Jui Hsieh; Inderjit S. Dhillon (ICML, 2016)

Square Root Graphical Models: Multivariate Generalizations of Univariate Exponential Families that Permit Positive Dependencies. - David I. Inouye; Pradeep Ravikumar; Inderjit S. Dhillon (ICML, 2016)

Optimal Classification with Multivariate Losses. - Nagarajan Natarajan; Oluwasanmi Koyejo; Pradeep Ravikumar; Inderjit S. Dhillon (ICML, 2016)

Computationally Efficient Nyström Approximation using Fast Transforms. - Si Si; Cho-Jui Hsieh; Inderjit S. Dhillon (ICML, 2016)

PD-Sparse : A Primal and Dual Sparse Approach to Extreme Multiclass and Multilabel Classification. - Ian En-Hsu Yen; Xiangru Huang; Pradeep Ravikumar; Kai Zhong; Inderjit S. Dhillon (ICML, 2016)

A Convex Atomic-Norm Approach to Multiple Sequence Alignment and Motif Discovery. - Ian En-Hsu Yen; Xin Lin; Jiong Zhang; Pradeep Ravikumar; Inderjit S. Dhillon (ICML, 2016)

Goal-Directed Inductive Matrix Completion. - Si Si; Kai-Yang Chiang; Cho-Jui Hsieh; Nikhil Rao 001; Inderjit S. Dhillon (KDD, 2016)

Structured Sparse Regression via Greedy Hard Thresholding. - Prateek Jain 002; Nikhil Rao 001; Inderjit S. Dhillon (NIPS, 2016)

Coordinate-wise Power Method. - Qi Lei; Kai Zhong; Inderjit S. Dhillon (NIPS, 2016)

Dual Decomposed Learning with Factorwise Oracle for Structural SVM of Large Output Domain. - Ian En-Hsu Yen; Xiangru Huang; Kai Zhong; Ruohan Zhang; Pradeep Ravikumar; Inderjit S. Dhillon (NIPS, 2016)

Asynchronous Parallel Greedy Coordinate Descent. - Yang You 001; Xiangru Lian; Ji Liu 002; Hsiang-Fu Yu; Inderjit S. Dhillon; James Demmel; Cho-Jui Hsieh (NIPS, 2016)

Temporal Regularized Matrix Factorization for High-dimensional Time Series Prediction. - Hsiang-Fu Yu; Nikhil Rao 001; Inderjit S. Dhillon (NIPS, 2016)

Mixed Linear Regression with Multiple Components. - Kai Zhong; Prateek Jain 002; Inderjit S. Dhillon (NIPS, 2016)

Fast Multiplier Methods to Optimize Non-exhaustive, Overlapping Clustering. - Yangyang Hou; Joyce Jiyoung Whang; David F. Gleich; Inderjit S. Dhillon (SDM, 2016)

Nomadic Computing for Big Data Analytics. - Hsiang-Fu Yu; Cho-Jui Hsieh; Hyokun Yun; S. V. N. Vishwanathan; Inderjit S. Dhillon (Computer, 2016)

Communication-Efficient Parallel Block Minimization for Kernel Machines. - Cho-Jui Hsieh; Si Si; Inderjit S. Dhillon (CoRR, 2016)

Kernel Ridge Regression via Partitioning. - Rashish Tandon; Si Si; Pradeep Ravikumar; Inderjit S. Dhillon (CoRR, 2016)

Clustered Matrix Approximation. - Berkant Savas; Inderjit S. Dhillon (SIAM J. Matrix Anal. Appl., 2016)

Overlapping Community Detection Using Neighborhood-Inflated Seed Expansion. - Joyce Jiyoung Whang; David F. Gleich; Inderjit S. Dhillon (IEEE Trans. Knowl. Data Eng., 2016)

Efficient and Non-Convex Coordinate Descent for Symmetric Nonnegative Matrix Factorization. - Arnaud Vandaele; Nicolas Gillis; Qi Lei; Kai Zhong; Inderjit S. Dhillon (IEEE Trans. Signal Process., 2016)

A Unified Algorithm for One-Cass Structured Matrix Factorization with Side Information. - Hsiang-Fu Yu; Hsin-Yuan Huang; Inderjit S. Dhillon; Chih-Jen Lin (AAAI, 2017)

Rank Aggregation and Prediction with Item Features. - Kai-Yang Chiang; Cho-Jui Hsieh; Inderjit S. Dhillon (AISTATS, 2017)

Greedy Direction Method of Multiplier for MAP Inference of Large Output Domain. - Xiangru Huang; Ian En-Hsu Yen; Ruohan Zhang; Qixing Huang; Pradeep Ravikumar; Inderjit S. Dhillon (AISTATS, 2017)

Scalable Convex Multiple Sequence Alignment via Entropy-Regularized Dual Decomposition. - Jiong Zhang; Ian En-Hsu Yen; Pradeep Ravikumar; Inderjit S. Dhillon (AISTATS, 2017)

Fast Classification with Binary Prototypes. - Kai Zhong; Ruiqi Guo; Sanjiv Kumar; Bowei Yan; David Simcha; Inderjit S. Dhillon (AISTATS, 2017)

Non-Exhaustive, Overlapping Co-Clustering. - Joyce Jiyoung Whang; Inderjit S. Dhillon (CIKM, 2017)

Doubly Greedy Primal-Dual Coordinate Descent for Sparse Empirical Risk Minimization. - Qi Lei; Ian En-Hsu Yen; Chao-Yuan Wu; Inderjit S. Dhillon; Pradeep Ravikumar (ICML, 2017)

Gradient Boosted Decision Trees for High Dimensional Sparse Output. - Si Si; Huan Zhang 001; S. Sathiya Keerthi; Dhruv Mahajan 001; Inderjit S. Dhillon; Cho-Jui Hsieh (ICML, 2017)

Recovery Guarantees for One-hidden-layer Neural Networks. - Kai Zhong; Zhao Song 002; Prateek Jain 002; Peter L. Bartlett; Inderjit S. Dhillon (ICML, 2017)

Communication-Efficient Distributed Block Minimization for Nonlinear Kernel Machines. - Cho-Jui Hsieh; Si Si; Inderjit S. Dhillon (KDD, 2017)

PPDsparse: A Parallel Primal-Dual Sparse Method for Extreme Classification. - Ian En-Hsu Yen; Xiangru Huang; Wei Dai 003; Pradeep Ravikumar; Inderjit S. Dhillon; Eric P. Xing (KDD, 2017)

A Greedy Approach for Budgeted Maximum Inner Product Search. - Hsiang-Fu Yu; Cho-Jui Hsieh; Qi Lei; Inderjit S. Dhillon (NIPS, 2017)

Similarity Preserving Representation Learning for Time Series Analysis. - Qi Lei; Jinfeng Yi; Roman Vaculín; Lingfei Wu 001; Inderjit S. Dhillon (CoRR, 2017)

Learning Non-overlapping Convolutional Neural Networks with Multiple Kernels. - Kai Zhong; Zhao Song 002; Inderjit S. Dhillon (CoRR, 2017)

Cost-Sensitive Learning with Noisy Labels. - Nagarajan Natarajan; Inderjit S. Dhillon; Pradeep Ravikumar; Ambuj Tewari (J. Mach. Learn. Res., 2017)

Memory Efficient Kernel Approximation. - Si Si; Cho-Jui Hsieh; Inderjit S. Dhillon (J. Mach. Learn. Res., 2017)

Partial Hard Thresholding. - Prateek Jain 002; Ambuj Tewari; Inderjit S. Dhillon (IEEE Trans. Inf. Theory, 2017)

Towards Fast Computation of Certified Robustness for ReLU Networks. - Tsui-Wei Weng; Huan Zhang 001; Hongge Chen; Zhao Song 002; Cho-Jui Hsieh; Luca Daniel; Duane S. Boning; Inderjit S. Dhillon (ICML, 2018)

Stabilizing Gradients for Deep Neural Networks via Efficient SVD Parameterization. - Jiong Zhang; Qi Lei; Inderjit S. Dhillon (ICML, 2018)

Learning Long Term Dependencies via Fourier Recurrent Units. - Jiong Zhang; Yibo Lin; Zhao Song 002; Inderjit S. Dhillon (ICML, 2018)

Realtime Query Completion via Deep Language Models. - Po-Wei Wang; Huan Zhang 001; Vijai Mohan; Inderjit S. Dhillon; J. Zico Kolter (eCOM@SIGIR, 2018)

Nonlinear Inductive Matrix Completion based on One-layer Neural Networks. - Kai Zhong; Zhao Song 002; Prateek Jain 002; Inderjit S. Dhillon (CoRR, 2018)

Discrete Attacks and Submodular Optimization with Applications to Text Classification. - Qi Lei; Lingfei Wu 001; Pin-Yu Chen; Alexandros G. Dimakis; Inderjit S. Dhillon; Michael Witbrock (CoRR, 2018)

Using Side Information to Reliably Learn Low-Rank Matrices from Missing and Corrupted Observations. - Kai-Yang Chiang; Inderjit S. Dhillon; Cho-Jui Hsieh (J. Mach. Learn. Res., 2018)

Online Embedding Compression for Text Classification Using Low Rank Matrix Factorization. - Anish Acharya; Rahul Goel; Angeliki Metallinou; Inderjit S. Dhillon (AAAI, 2019)

Parallel Asynchronous Stochastic Coordinate Descent with Auxiliary Variables. - Hsiang-Fu Yu; Cho-Jui Hsieh; Inderjit S. Dhillon (AISTATS, 2019)

Extreme Stochastic Variational Inference: Distributed Inference for Large Scale Mixture Models. - Jiong Zhang; Parameswaran Raman; Shihao Ji 001; Hsiang-Fu Yu; S. V. N. Vishwanathan; Inderjit S. Dhillon (AISTATS, 2019)

Abstract of the Keynotes. - Inderjit S. Dhillon (IC3, 2019)

The Limitations of Adversarial Training and the Blind-Spot Attack. - Huan Zhang 001; Hongge Chen; Zhao Song 002; Duane S. Boning; Inderjit S. Dhillon; Cho-Jui Hsieh (ICLR (Poster), 2019)

Similarity Preserving Representation Learning for Time Series Clustering. - Qi Lei; Jinfeng Yi; Roman Vaculín; Lingfei Wu 001; Inderjit S. Dhillon (IJCAI, 2019)

Discrete Adversarial Attacks and Submodular Optimization with Applications to Text Classification. - Qi Lei; Lingfei Wu 001; Pin-Yu Chen; Alex Dimakis; Inderjit S. Dhillon; Michael Witbrock (SysML, 2019)

Inverting Deep Generative models, One layer at a time. - Qi Lei; Ajil Jalal; Inderjit S. Dhillon; Alexandros G. Dimakis (NeurIPS, 2019)

Primal-Dual Block Generalized Frank-Wolfe. - Qi Lei; Jiacheng Zhuo; Constantine Caramanis; Inderjit S. Dhillon; Alexandros G. Dimakis (NeurIPS, 2019)

Think Globally, Act Locally: A Deep Neural Network Approach to High-Dimensional Time Series Forecasting. - Rajat Sen; Hsiang-Fu Yu; Inderjit S. Dhillon (NeurIPS, 2019)

AutoAssist: A Framework to Accelerate Training of Deep Neural Networks. - Jiong Zhang; Hsiang-Fu Yu; Inderjit S. Dhillon (NeurIPS, 2019)

Provable Non-linear Inductive Matrix Completion. - Kai Zhong; Zhao Song 002; Prateek Jain 002; Inderjit S. Dhillon (NeurIPS, 2019)

SysML: The New Frontier of Machine Learning Systems. - Alexander Ratner; Dan Alistarh; Gustavo Alonso; David G. Andersen; Peter Bailis; Sarah Bird; Nicholas Carlini; Bryan Catanzaro; Eric S. Chung; Bill Dally; Jeff Dean; Inderjit S. Dhillon; et al. (CoRR, 2019)

A Modular Deep Learning Approach for Extreme Multi-label Text Classification. - Wei-Cheng Chang; Hsiang-Fu Yu; Kai Zhong; Yiming Yang; Inderjit S. Dhillon (CoRR, 2019)

Primal-Dual Block Frank-Wolfe. - Qi Lei; Jiacheng Zhuo; Constantine Caramanis; Inderjit S. Dhillon; Alexandros G. Dimakis (CoRR, 2019)

Multiresolution Transformer Networks: Recurrence is Not Essential for Modeling Hierarchical Structure. - Vikas K. Garg 001; Inderjit S. Dhillon; Hsiang-Fu Yu (CoRR, 2019)

Non-Exhaustive, Overlapping Clustering. - Joyce Jiyoung Whang; Yangyang Hou; David F. Gleich; Inderjit S. Dhillon (IEEE Trans. Pattern Anal. Mach. Intell., 2019)

Learning to Encode Position for Transformer with Continuous Dynamical Model. - Xuanqing Liu; Hsiang-Fu Yu; Inderjit S. Dhillon; Cho-Jui Hsieh (ICML, 2020)

Extreme Multi-label Classification from Aggregated Labels. - Yanyao Shen; Hsiang-Fu Yu; Sujay Sanghavi; Inderjit S. Dhillon (ICML, 2020)

Taming Pretrained Transformers for Extreme Multi-label Text Classification. - Wei-Cheng Chang; Hsiang-Fu Yu; Kai Zhong; Yiming Yang; Inderjit S. Dhillon (KDD, 2020)

Scalable Anti-TrustRank with Qualified Site-level Seeds for Link-based Web Spam Detection. - Joyce Jiyoung Whang; Yeonsung Jung; Seonggoo Kang; Dongho Yoo; Inderjit S. Dhillon (WWW (Companion Volume), 2020)

Non-Exhaustive, Overlapping Co-Clustering: An Extended Analysis. - Joyce Jiyoung Whang; Inderjit S. Dhillon (CoRR, 2020)

PECOS: Prediction for Enormous and Correlated Output Spaces. - Hsiang-Fu Yu; Kai Zhong; Inderjit S. Dhillon (CoRR, 2020)

On the Benefits of Multiple Gossip Steps in Communication-Constrained Decentralized Optimization. - Abolfazl Hashemi; Anish Acharya; Rudrajit Das; Haris Vikalo; Sujay Sanghavi; Inderjit S. Dhillon (CoRR, 2020)

Voting based ensemble improves robustness of defensive models. - Devvrit; Minhao Cheng; Cho-Jui Hsieh; Inderjit S. Dhillon (CoRR, 2020)

Improved Convergence Rates for Non-Convex Federated Learning with Compression. - Rudrajit Das; Abolfazl Hashemi; Sujay Sanghavi; Inderjit S. Dhillon (CoRR, 2020)

Learning from eXtreme Bandit Feedback. - Romain Lopez; Inderjit S. Dhillon; Michael I. Jordan (AAAI, 2021)

Enabling Efficiency-Precision Trade-offs for Label Trees in Extreme Classification. - Tavor Z. Baharav; Daniel L. Jiang; Kedarnath Kolluri; Sujay Sanghavi; Inderjit S. Dhillon (CIKM, 2021)

Top-k eXtreme Contextual Bandits with Arm Hierarchy. - Rajat Sen; Alexander Rakhlin; Lexing Ying; Rahul Kidambi; Dean P. Foster; Daniel N. Hill; Inderjit S. Dhillon (ICML, 2021)

Extreme Multi-label Learning for Semantic Matching in Product Search. - Wei-Cheng Chang; Daniel L. Jiang; Hsiang-Fu Yu; Choon-Hui Teo; Jiong Zhang; Kai Zhong; Kedarnath Kolluri; Qie Hu; Nikhil Shandilya; Vyacheslav Ievgrafov; Japinder Singh; Inderjit S. Dhillon (KDD, 2021)

Session-Aware Query Auto-completion using Extreme Multi-Label Ranking. - Nishant Yadav; Rajat Sen; Daniel N. Hill; Arya Mazumdar; Inderjit S. Dhillon (KDD, 2021)

DRONE: Data-aware Low-rank Compression for Large NLP Models. - Patrick H. Chen; Hsiang-Fu Yu; Inderjit S. Dhillon; Cho-Jui Hsieh (NeurIPS, 2021)

Label Disentanglement in Partition-based Extreme Multilabel Classification. - Xuanqing Liu; Wei-Cheng Chang; Hsiang-Fu Yu; Cho-Jui Hsieh; Inderjit S. Dhillon (NeurIPS, 2021)

Fast Multi-Resolution Transformer Fine-tuning for Extreme Multi-label Text Classification. - Jiong Zhang; Wei-Cheng Chang; Hsiang-Fu Yu; Inderjit S. Dhillon (NeurIPS, 2021)

Combinatorial Bandits without Total Order for Arms. - Shuo Yang; Tongzheng Ren; Inderjit S. Dhillon; Sujay Sanghavi (CoRR, 2021)

Accelerating Inference for Sparse Extreme Multi-Label Ranking Trees. - Philip A. Etter; Kai Zhong; Hsiang-Fu Yu; Lexing Ying; Inderjit S. Dhillon (CoRR, 2021)

DP-NormFedAvg: Normalizing Client Updates for Privacy-Preserving Federated Learning. - Rudrajit Das; Abolfazl Hashemi; Sujay Sanghavi; Inderjit S. Dhillon (CoRR, 2021)

Quasi-Newton policy gradient algorithms. - Haoya Li; Samarth Gupta; Hsiang-Fu Yu; Lexing Ying; Inderjit S. Dhillon (CoRR, 2021)

Cluster-and-Conquer: A Framework For Time-Series Forecasting. - Reese Pathak; Rajat Sen; Nikhil Rao 001; N. Benjamin Erichson; Michael I. Jordan; Inderjit S. Dhillon (CoRR, 2021)

Robust Training in High Dimensions via Block Coordinate Geometric Median Descent. - Anish Acharya; Abolfazl Hashemi; Prateek Jain 002; Sujay Sanghavi; Inderjit S. Dhillon; Ufuk Topcu (AISTATS, 2022)

Node Feature Extraction by Self-Supervised Multi-scale Neighborhood Prediction. - Eli Chien; Wei-Cheng Chang; Cho-Jui Hsieh; Hsiang-Fu Yu; Jiong Zhang; Olgica Milenkovic; Inderjit S. Dhillon (ICLR, 2022)

Linear Bandit Algorithms with Sublinear Time Complexity. - Shuo Yang; Tongzheng Ren; Sanjay Shakkottai; Eric Price 001; Inderjit S. Dhillon; Sujay Sanghavi (ICML, 2022)

CAT: Customized Adversarial Training for Improved Robustness. - Minhao Cheng; Qi Lei; Pin-Yu Chen; Inderjit S. Dhillon; Cho-Jui Hsieh (IJCAI, 2022)

Extreme Zero-Shot Learning for Extreme Text Classification. - Yuanhao Xiong; Wei-Cheng Chang; Cho-Jui Hsieh; Hsiang-Fu Yu; Inderjit S. Dhillon (NAACL-HLT, 2022)

S3GC: Scalable Self-Supervised Graph Clustering. - Devvrit; Aditya Sinha; Inderjit S. Dhillon; Prateek Jain 002 (NeurIPS, 2022)

ELIAS: End-to-End Learning to Index and Search in Large Output Spaces. - Nilesh Gupta; Patrick H. Chen; Hsiang-Fu Yu; Cho-Jui Hsieh; Inderjit S. Dhillon (NeurIPS, 2022)

Counterfactual Learning To Rank for Utility-Maximizing Query Autocompletion. - Adam Block; Rahul Kidambi; Daniel N. Hill; Thorsten Joachims; Inderjit S. Dhillon (SIGIR, 2022)

Faster non-convex federated learning via global and local momentum. - Rudrajit Das; Anish Acharya; Abolfazl Hashemi; Sujay Sanghavi; Inderjit S. Dhillon; Ufuk Topcu (UAI, 2022)

Enterprise-Scale Search: Accelerating Inference for Sparse Extreme Multi-Label Ranking Trees. - Philip A. Etter; Kai Zhong; Hsiang-Fu Yu; Lexing Ying; Inderjit S. Dhillon (WWW, 2022)

Positive Unlabeled Contrastive Learning. - Anish Acharya; Sujay Sanghavi; Li Jing 001; Bhargav Bhushanam; Dhruv Choudhary; Michael G. Rabbat; Inderjit S. Dhillon (CoRR, 2022)

FINGER: Fast Inference for Graph-based Approximate Nearest Neighbor Search. - Patrick H. Chen; Wei-Cheng Chang; Hsiang-Fu Yu; Inderjit S. Dhillon; Cho-Jui Hsieh (CoRR, 2022)

End-to-End Learning to Index and Search in Large Output Spaces. - Nilesh Gupta; Patrick H. Chen; Hsiang-Fu Yu; Cho-Jui Hsieh; Inderjit S. Dhillon (CoRR, 2022)

Preserving In-Context Learning ability in Large Language Model Fine-tuning. - Yihan Wang; Si Si; Daliang Li; Michal Lukasik; Felix X. Yu; Cho-Jui Hsieh; Inderjit S. Dhillon; Sanjiv Kumar (CoRR, 2022)

PECOS: Prediction for Enormous and Correlated Output Spaces. - Hsiang-Fu Yu; Kai Zhong; Jiong Zhang; Wei-Cheng Chang; Inderjit S. Dhillon (J. Mach. Learn. Res., 2022)

On the Benefits of Multiple Gossip Steps in Communication-Constrained Decentralized Federated Learning. - Abolfazl Hashemi; Anish Acharya; Rudrajit Das; Haris Vikalo; Sujay Sanghavi; Inderjit S. Dhillon (IEEE Trans. Parallel Distributed Syst., 2022)

Sample Efficiency of Data Augmentation Consistency Regularization. - Shuo Yang; Yijun Dong; Rachel A. Ward; Inderjit S. Dhillon; Sujay Sanghavi; Qi Lei (AISTATS, 2023)

A Computationally Efficient Sparsified Online Newton Method. - Devvrit; Sai Surya Duvvuri; Rohan Anil; Vineet Gupta 001; Cho-Jui Hsieh; Inderjit S. Dhillon (NeurIPS, 2023)

Block Low-Rank Preconditioner with Shared Basis for Stochastic Optimization. - Jui-Nan Yen; Sai Surya Duvvuri; Inderjit S. Dhillon; Cho-Jui Hsieh (NeurIPS, 2023)

FINGER: Fast Inference for Graph-based Approximate Nearest Neighbor Search. - Patrick H. Chen; Wei-Cheng Chang; Jyun-Yu Jiang; Hsiang-Fu Yu; Inderjit S. Dhillon; Cho-Jui Hsieh (WWW, 2023)

Efficacy of Dual-Encoders for Extreme Multi-Label Classification. - Nilesh Gupta; Devvrit Khatri; Ankit Singh Rawat; Srinadh Bhojanapalli; Prateek Jain 002; Inderjit S. Dhillon (CoRR, 2023)

Approximate Newton Policy Gradient Algorithms. - Haoya Li; Samarth Gupta; Hsiang-Fu Yu; Lexing Ying; Inderjit S. Dhillon (SIAM J. Sci. Comput., 2023)

Automatic Engineering of Long Prompts. - Cho-Jui Hsieh; Si Si; Felix X. Yu; Inderjit S. Dhillon (ACL (Findings), 2024)

PRISM: A New Lens for Improved Color Understanding. - Arjun R. Akula; Garima Pruthi; Inderjit S. Dhillon; Pradyumna Narayana; Sugato Basu; Varun Jampani (EMNLP (Industry Track), 2024)

Combining Axes Preconditioners through Kronecker Approximation for Deep Learning. - Sai Surya Duvvuri; Devvrit; Rohan Anil; Cho-Jui Hsieh; Inderjit S. Dhillon (ICLR, 2024)

Dual-Encoders for Extreme Multi-label Classification. - Nilesh Gupta; Devvrit; Ankit Singh Rawat; Srinadh Bhojanapalli; Prateek Jain 002; Inderjit S. Dhillon (ICLR, 2024)

Two-stage LLM Fine-tuning with Less Specialization and More Generalization. - Yihan Wang; Si Si; Daliang Li; Michal Lukasik; Felix X. Yu; Cho-Jui Hsieh; Inderjit S. Dhillon; Sanjiv Kumar (ICLR, 2024)

MatFormer: Nested Transformer for Elastic Inference. - Devvrit; Sneha Kudugunta; Aditya Kusupati; Tim Dettmers; Kaifeng Chen; Inderjit S. Dhillon; Yulia Tsvetkov; Hanna Hajishirzi; Sham M. Kakade; Ali Farhadi; Prateek Jain 002 (NeurIPS, 2024)

Towards Quantifying the Preconditioning Effect of Adam. - Rudrajit Das; Naman Agarwal; Sujay Sanghavi; Inderjit S. Dhillon (CoRR, 2024)

Retraining with Predicted Hard Labels Provably Increases Model Accuracy. - Rudrajit Das; Inderjit S. Dhillon; Alessandro Epasto; Adel Javanmard; Jieming Mao; Vahab Mirrokni; Sujay Sanghavi; Peilin Zhong (CoRR, 2024)

Geometric Median (GM) Matching for Robust Data Pruning. - Anish Acharya; Inderjit S. Dhillon; Sujay Sanghavi (CoRR, 2024)

LASER: Attention with Exponential Transformation. - Sai Surya Duvvuri; Inderjit S. Dhillon (CoRR, 2024)

EHI: End-to-end Learning of Hierarchical Index for Efficient Dense Retrieval. - Ramnath Kumar; Anshul Mittal; Nilesh Gupta; Aditya Kusupati; Inderjit S. Dhillon; Prateek Jain 002 (Trans. Mach. Learn. Res., 2024)

Accelerating Primal-Dual Methods for Regularized Markov Decision Processes. - Haoya Li; Hsiang-Fu Yu; Lexing Ying; Inderjit S. Dhillon (SIAM J. Optim., 2024)

Large Language Models are Interpretable Learners. - Ruochen Wang; Si Si; Felix X. Yu; Dorothea Wiesmann Rothuizen; Cho-Jui Hsieh; Inderjit S. Dhillon (ICLR, 2025)

LoRA Done RITE: Robust Invariant Transformation Equilibration for LoRA Optimization. - Jui-Nan Yen; Si Si; Zhao Meng; Felix X. Yu; Sai Surya Duvvuri; Inderjit S. Dhillon; Cho-Jui Hsieh; Sanjiv Kumar (ICLR, 2025)

Geometric Median Matching for Robust k-Subset Selection from Noisy Data. - Anish Acharya; Sujay Sanghavi; Alexandros G. Dimakis; Inderjit S. Dhillon (CoRR, 2025)

Matryoshka Model Learning for Improved Elastic Student Models. - Chetan Verma; Aditya Srinivas Timmaraju; Cho-Jui Hsieh; Suyash Damle; Ngot Bui; Yang Zhang; Wen Chen; Xin Liu; Prateek Jain 002; Inderjit S. Dhillon (CoRR, 2025)

Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities. - Gheorghe Comanici; Eric Bieber; Mike Schaekermann; Ice Pasupat; Noveen Sachdeva; Inderjit S. Dhillon; Marcel Blistein; Ori Ram; Dan Zhang; Evan Rosen; Luke Marris; Sam Petulla; et al. (CoRR, 2025)