Dhillon, Inderjit S.

103 publications

ICML 2025 Geometric Median (GM) Matching for Robust K-Subset Selection from Noisy Data Anish Acharya, Sujay Sanghavi, Alex Dimakis, Inderjit S Dhillon

ICML 2025 LASER: Attention with Exponential Transformation Sai Surya Duvvuri, Inderjit S Dhillon

ICLR 2025 Large Language Models Are Interpretable Learners Ruochen Wang, Si Si, Felix 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 Yu, Sai Surya Duvvuri, Inderjit S Dhillon, Cho-Jui Hsieh, Sanjiv Kumar

ICML 2025 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

NeurIPS 2025 Scalable In-Context Ranking with Generative Models Nilesh Gupta, Chong You, Srinadh Bhojanapalli, Sanjiv Kumar, Inderjit S Dhillon, Felix X. Yu

ICLR 2024 Combining Axes Preconditioners Through Kronecker Approximation for Deep Learning Sai Surya Duvvuri, Fnu Devvrit, Rohan Anil, Cho-Jui Hsieh, Inderjit S Dhillon

ICLR 2024 Dual-Encoders for Extreme Multi-Label Classification Nilesh Gupta, Fnu Devvrit, Ankit Singh Rawat, Srinadh Bhojanapalli, Prateek Jain, Inderjit S Dhillon

TMLR 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

ICMLW 2024 Geometric Median Matching for Robust Data Pruning Anish Acharya, Inderjit S Dhillon, Sujay Sanghavi

ICLR 2024 Two-Stage LLM Fine-Tuning with Less Specialization and More Generalization Yihan Wang, Si Si, Daliang Li, Michal Lukasik, Felix Yu, Cho-Jui Hsieh, Inderjit S Dhillon, Sanjiv Kumar

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

ICLRW 2023 Bayesian Regularization of Empirical MDPs Samarth Gupta, Daniel N. Hill, Lexing Ying, 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

NeurIPSW 2023 MatFormer: Nested Transformer for Elastic Inference Fnu Devvrit, Sneha Kudugunta, Aditya Kusupati, Tim Dettmers, Kaifeng Chen, Inderjit S Dhillon, Yulia Tsvetkov, Hannaneh Hajishirzi, Sham M. Kakade, Ali Farhadi, Prateek Jain

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

NeurIPSW 2023 Two-Stage LLM Fine-Tuning with Less Specialization and More Generalization Yihan Wang, Si Si, Daliang Li, Michal Lukasik, Felix Yu, Cho-Jui Hsieh, Inderjit S Dhillon, Sanjiv Kumar

ICMLW 2023 UCB Provably Learns from Inconsistent Human Feedback Shuo Yang, Tongzheng Ren, Inderjit S Dhillon, Sujay Sanghavi

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

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

NeurIPSW 2022 Differentially Private Federated Learning with Normalized Updates Rudrajit Das, Abolfazl Hashemi, Sujay Sanghavi, Inderjit S Dhillon

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

UAI 2022 Faster Non-Convex Federated Learning via Global and Local Momentum Rudrajit Das, Anish Acharya, Abolfazl Hashemi, Sujay Sanghavi, Inderjit S. Dhillon, Ufuk Topcu

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

ICLR 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

JMLR 2022 PECOS: Prediction for Enormous and Correlated Output Spaces Hsiang-Fu Yu, Kai Zhong, Jiong Zhang, Wei-Cheng Chang, Inderjit S. Dhillon

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

NeurIPS 2021 DRONE: Data-Aware Low-Rank Compression for Large NLP Models Patrick Chen, Hsiang-Fu Yu, Inderjit S. Dhillon, Cho-Jui Hsieh

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 Label Disentanglement in Partition-Based Extreme Multilabel Classification Xuanqing Liu, Wei-Cheng Chang, Hsiang-Fu Yu, Cho-Jui Hsieh, Inderjit S. Dhillon

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

ICML 2021 Top-K eXtreme Contextual Bandits with Arm Hierarchy Rajat Sen, Alexander Rakhlin, Lexing Ying, Rahul Kidambi, Dean Foster, Daniel N Hill, 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 Inverting Deep Generative Models, One Layer at a Time Qi Lei, Ajil Jalal, Inderjit S Dhillon, Alexandros G Dimakis

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

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

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

NeurIPS 2019 Provable Non-Linear Inductive Matrix Completion Kai Zhong, Zhao Song, Prateek Jain, Inderjit S Dhillon

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

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

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

JMLR 2018 Using Side Information to Reliably Learn Low-Rank Matrices from Missing and Corrupted Observations Kai-Yang Chiang, Inderjit S. Dhillon, Cho-Jui Hsieh

NeurIPS 2017 A Greedy Approach for Budgeted Maximum Inner Product Search Hsiang-Fu Yu, Cho-Jui Hsieh, Qi Lei, Inderjit S Dhillon

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

ICML 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

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

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

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

JMLR 2017 Memory Efficient Kernel Approximation Si Si, Cho-Jui Hsieh, Inderjit S. Dhillon

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

ICML 2017 Recovery Guarantees for One-Hidden-Layer Neural Networks Kai Zhong, Zhao Song, Prateek Jain, Peter L. Bartlett, 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

NeurIPS 2016 Asynchronous Parallel Greedy Coordinate Descent Yang You, Xiangru Lian, Ji Liu, Hsiang-Fu Yu, Inderjit S Dhillon, James Demmel, Cho-Jui Hsieh

NeurIPS 2016 Coordinate-Wise Power Method Qi Lei, Kai Zhong, Inderjit S Dhillon

NeurIPS 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 K Ravikumar, Inderjit S Dhillon

NeurIPS 2016 Mixed Linear Regression with Multiple Components Kai Zhong, Prateek Jain, Inderjit S Dhillon

NeurIPS 2016 Structured Sparse Regression via Greedy Hard Thresholding Prateek Jain, Nikhil Rao, Inderjit S Dhillon

NeurIPS 2016 Temporal Regularized Matrix Factorization for High-Dimensional Time Series Prediction Hsiang-Fu Yu, Nikhil Rao, Inderjit S Dhillon

NeurIPS 2015 Collaborative Filtering with Graph Information: Consistency and Scalable Methods Nikhil Rao, Hsiang-Fu Yu, Pradeep K Ravikumar, Inderjit S Dhillon

NeurIPS 2015 Consistent Multilabel Classification Oluwasanmi O Koyejo, Nagarajan Natarajan, Pradeep K Ravikumar, Inderjit S Dhillon

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

NeurIPS 2015 Fixed-Length Poisson MRF: Adding Dependencies to the Multinomial David I Inouye, Pradeep K Ravikumar, Inderjit S Dhillon

NeurIPS 2015 Matrix Completion with Noisy Side Information Kai-Yang Chiang, Cho-Jui Hsieh, Inderjit S Dhillon

NeurIPS 2015 Sparse Linear Programming via Primal and Dual Augmented Coordinate Descent Ian En-Hsu Yen, Kai Zhong, Cho-Jui Hsieh, Pradeep K Ravikumar, Inderjit S Dhillon

NeurIPS 2014 Capturing Semantically Meaningful Word Dependencies with an Admixture of Poisson MRFs David I Inouye, Pradeep K Ravikumar, Inderjit S Dhillon

NeurIPS 2014 Consistent Binary Classification with Generalized Performance Metrics Oluwasanmi O Koyejo, Nagarajan Natarajan, Pradeep K Ravikumar, Inderjit S Dhillon

NeurIPS 2014 Constant Nullspace Strong Convexity and Fast Convergence of Proximal Methods Under High-Dimensional Settings Ian En-Hsu Yen, Cho-Jui Hsieh, Pradeep K Ravikumar, Inderjit S Dhillon

NeurIPS 2014 Fast Prediction for Large-Scale Kernel Machines Cho-Jui Hsieh, Si Si, Inderjit S Dhillon

NeurIPS 2014 Multi-Scale Spectral Decomposition of Massive Graphs Si Si, Donghyuk Shin, Inderjit S Dhillon, Beresford N Parlett

JMLR 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

NeurIPS 2014 Proximal Quasi-Newton for Computationally Intensive L1-Regularized M-Estimators Kai Zhong, Ian En-Hsu Yen, Inderjit S Dhillon, Pradeep K Ravikumar

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

JMLR 2014 QUIC: Quadratic Approximation for Sparse Inverse Covariance Estimation Cho-Jui Hsieh, Mátyás A. Sustik, Inderjit S. Dhillon, Pradeep Ravikumar

NeurIPS 2014 Sparse Random Feature Algorithm as Coordinate Descent in Hilbert Space Ian En-Hsu Yen, Ting-Wei Lin, Shou-De Lin, Pradeep K Ravikumar, Inderjit S Dhillon

NeurIPS 2013 BIG & QUIC: Sparse Inverse Covariance Estimation for a Million Variables Cho-Jui Hsieh, Matyas A Sustik, Inderjit S Dhillon, Pradeep K Ravikumar, Russell Poldrack

NeurIPS 2013 Large Scale Distributed Sparse Precision Estimation Huahua Wang, Arindam Banerjee, Cho-Jui Hsieh, Pradeep K Ravikumar, Inderjit S Dhillon

NeurIPS 2013 Learning with Noisy Labels Nagarajan Natarajan, Inderjit S Dhillon, Pradeep K Ravikumar, Ambuj Tewari

NeurIPS 2012 A Divide-and-Conquer Method for Sparse Inverse Covariance Estimation Cho-jui Hsieh, Arindam Banerjee, Inderjit S. Dhillon, Pradeep K. Ravikumar

JMLR 2012 Metric and Kernel Learning Using a Linear Transformation Prateek Jain, Brian Kulis, Jason V. Davis, Inderjit S. Dhillon

NeurIPS 2011 Greedy Algorithms for Structurally Constrained High Dimensional Problems Ambuj Tewari, Pradeep K. Ravikumar, Inderjit S. Dhillon

NeurIPS 2011 Nearest Neighbor Based Greedy Coordinate Descent Inderjit S. Dhillon, Pradeep K. Ravikumar, Ambuj Tewari

NeurIPS 2011 Orthogonal Matching Pursuit with Replacement Prateek Jain, Ambuj Tewari, Inderjit S. Dhillon

NeurIPS 2011 Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation Cho-jui Hsieh, Inderjit S. Dhillon, Pradeep K. Ravikumar, Mátyás A. Sustik

ICML 2010 A Scalable Trust-Region Algorithm with Application to Mixed-Norm Regression Dongmin Kim, Suvrit Sra, Inderjit S. Dhillon

NeurIPS 2010 Guaranteed Rank Minimization via Singular Value Projection Prateek Jain, Raghu Meka, Inderjit S. Dhillon

NeurIPS 2010 Inductive Regularized Learning of Kernel Functions Prateek Jain, Brian Kulis, Inderjit S. Dhillon

ICML 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, Inderjit S. Dhillon

JMLR 2009 Low-Rank Kernel Learning with Bregman Matrix Divergences Brian Kulis, Mátyás A. Sustik, Inderjit S. Dhillon

NeurIPS 2009 Matrix Completion from Power-Law Distributed Samples Raghu Meka, Prateek Jain, Inderjit S. Dhillon

MLJ 2009 Semi-Supervised Graph Clustering: A Kernel Approach Brian Kulis, Sugato Basu, Inderjit S. Dhillon, Raymond J. Mooney

NeurIPS 2008 Online Metric Learning and Fast Similarity Search Prateek Jain, Brian Kulis, Inderjit S. Dhillon, Kristen Grauman

ICML 2008 Rank Minimization via Online Learning Raghu Meka, Prateek Jain, Constantine Caramanis, Inderjit S. Dhillon

ICML 2007 Information-Theoretic Metric Learning Jason V. Davis, Brian Kulis, Prateek Jain, Suvrit Sra, Inderjit S. Dhillon

NeurIPS 2006 Differential Entropic Clustering of Multivariate Gaussians Jason V. Davis, Inderjit S. Dhillon

ICML 2006 Learning Low-Rank Kernel Matrices Brian Kulis, Mátyás A. Sustik, Inderjit S. Dhillon

JMLR 2005 Clustering on the Unit Hypersphere Using Von Mises-Fisher Distributions Arindam Banerjee, Inderjit S. Dhillon, Joydeep Ghosh, Suvrit Sra

JMLR 2005 Clustering with Bregman Divergences Arindam Banerjee, Srujana Merugu, Inderjit S. Dhillon, Joydeep Ghosh

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

ICML 2005 Semi-Supervised Graph Clustering: A Kernel Approach Brian Kulis, Sugato Basu, Inderjit S. Dhillon, Raymond J. Mooney

ICML 2004 An Information Theoretic Analysis of Maximum Likelihood Mixture Estimation for Exponential Families Arindam Banerjee, Inderjit S. Dhillon, Joydeep Ghosh, Srujana Merugu

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

MLJ 2001 Concept Decompositions for Large Sparse Text Data Using Clustering Inderjit S. Dhillon, Dharmendra S. Modha