Inderjit S. Dhillon

ORCID

Publication Activity (10 Years)

Years Active: 1995-2024
Publications (10 Years): 147

Top Venues

Publications

Nilesh Gupta, Devvrit, Ankit Singh Rawat, Srinadh Bhojanapalli, Prateek Jain, Inderjit S. Dhillon
Dual-Encoders for Extreme Multi-label Classification. ICLR (2024)
Sai Surya Duvvuri, Devvrit, Rohan Anil, Cho-Jui Hsieh, Inderjit S. Dhillon
Combining Axes Preconditioners through Kronecker Approximation for Deep Learning. ICLR (2024)
Haoya Li, Hsiang-Fu Yu, Lexing Ying, Inderjit S. Dhillon
Accelerating Primal-Dual Methods for Regularized Markov Decision Processes. SIAM J. Optim. 34 (1) (2024)
Rudrajit Das, Inderjit S. Dhillon, Alessandro Epasto, Adel Javanmard, Jieming Mao, Vahab Mirrokni, Sujay Sanghavi, Peilin Zhong
Retraining with Predicted Hard Labels Provably Increases Model Accuracy. CoRR (2024)
Ruochen Wang, Si Si, Felix Yu, Dorothea Wiesmann, Cho-Jui Hsieh, Inderjit S. Dhillon
Large Language Models are Interpretable Learners. CoRR (2024)
Cho-Jui Hsieh, Si Si, Felix Yu, Inderjit S. Dhillon
Automatic Engineering of Long Prompts. ACL (Findings) (2024)
Anish Acharya, Inderjit S. Dhillon, Sujay Sanghavi
Geometric Median (GM) Matching for Robust Data Pruning. CoRR (2024)
Yihan Wang, Si Si, Daliang Li, Michal Lukasik, Felix Yu, Cho-Jui Hsieh, Inderjit S. Dhillon, Sanjiv Kumar
Two-stage LLM Fine-tuning with Less Specialization and More Generalization. ICLR (2024)
Rudrajit Das, Naman Agarwal, Sujay Sanghavi, Inderjit S. Dhillon
Towards Quantifying the Preconditioning Effect of Adam. CoRR (2024)
Shuo Yang, Yijun Dong, Rachel Ward, Inderjit S. Dhillon, Sujay Sanghavi, Qi Lei
Sample Efficiency of Data Augmentation Consistency Regularization. AISTATS (2023)
Cho-Jui Hsieh, Si Si, Felix X. Yu, Inderjit S. Dhillon
Automatic Engineering of Long Prompts. CoRR (2023)
Haoya Li, Samarth Gupta, Hsiang-Fu Yu, Lexing Ying, Inderjit S. Dhillon
Approximate Newton Policy Gradient Algorithms. SIAM J. Sci. Comput. 45 (5) (2023)
Fnu Devvrit, Sai Surya Duvvuri, Rohan Anil, Vineet Gupta, Cho-Jui Hsieh, Inderjit S. Dhillon
A Computationally Efficient Sparsified Online Newton Method. CoRR (2023)
Patrick H. Chen, Wei-Cheng Chang, Jyun-Yu Jiang, Hsiang-Fu Yu, Inderjit S. Dhillon, Cho-Jui Hsieh
FINGER: Fast Inference for Graph-based Approximate Nearest Neighbor Search. WWW (2023)
Nilesh Gupta, Devvrit Khatri, Ankit S. Rawat, Srinadh Bhojanapalli, Prateek Jain, Inderjit S. Dhillon
Efficacy of Dual-Encoders for Extreme Multi-Label Classification. CoRR (2023)
Ramnath Kumar, Anshul Mittal, Nilesh Gupta, Aditya Kusupati, Inderjit S. Dhillon, Prateek Jain
EHI: End-to-end Learning of Hierarchical Index for Efficient Dense Retrieval. CoRR (2023)
Fnu Devvrit, Sai Surya Duvvuri, Rohan Anil, Vineet Gupta, Cho-Jui Hsieh, Inderjit S. Dhillon
A Computationally Efficient Sparsified Online Newton Method. NeurIPS (2023)
Jui-Nan Yen, Sai Surya Duvvuri, Inderjit S. Dhillon, Cho-Jui Hsieh
Block Low-Rank Preconditioner with Shared Basis for Stochastic Optimization. NeurIPS (2023)
Devvrit, Sneha Kudugunta, Aditya Kusupati, Tim Dettmers, Kaifeng Chen, Inderjit S. Dhillon, Yulia Tsvetkov, Hannaneh Hajishirzi, Sham M. Kakade, Ali Farhadi, Prateek Jain
MatFormer: Nested Transformer for Elastic Inference. CoRR (2023)
Anish Acharya, Abolfazl Hashemi, Prateek Jain, Sujay Sanghavi, Inderjit S. Dhillon, Ufuk Topcu
Robust Training in High Dimensions via Block Coordinate Geometric Median Descent. AISTATS (2022)
Abolfazl Hashemi, Anish Acharya, Rudrajit Das, Haris Vikalo, Sujay Sanghavi, Inderjit S. Dhillon
On the Benefits of Multiple Gossip Steps in Communication-Constrained Decentralized Federated Learning. IEEE Trans. Parallel Distributed Syst. 33 (11) (2022)
Yuanhao Xiong, Wei-Cheng Chang, Cho-Jui Hsieh, Hsiang-Fu Yu, Inderjit S. Dhillon
Extreme Zero-Shot Learning for Extreme Text Classification. NAACL-HLT (2022)
Fnu Devvrit, Aditya Sinha, Inderjit S. Dhillon, Prateek Jain
S3GC: Scalable Self-Supervised Graph Clustering. NeurIPS (2022)
Eli Chien, Wei-Cheng Chang, Cho-Jui Hsieh, Hsiang-Fu Yu, Jiong Zhang, Olgica Milenkovic, Inderjit S. Dhillon
Node Feature Extraction by Self-Supervised Multi-scale Neighborhood Prediction. ICLR (2022)
Adam Block, Rahul Kidambi, Daniel N. Hill, Thorsten Joachims, Inderjit S. Dhillon
Counterfactual Learning To Rank for Utility-Maximizing Query Autocompletion. CoRR (2022)
Hsiang-Fu Yu, Kai Zhong, Jiong Zhang, Wei-Cheng Chang, Inderjit S. Dhillon
PECOS: Prediction for Enormous and Correlated Output Spaces. J. Mach. Learn. Res. 23 (2022)
Philip A. Etter, Kai Zhong, Hsiang-Fu Yu, Lexing Ying, Inderjit S. Dhillon
Enterprise-Scale Search: Accelerating Inference for Sparse Extreme Multi-Label Ranking Trees. WWW (2022)
Yihan Wang, Si Si, Daliang Li, Michal Lukasik, Felix X. Yu, Cho-Jui Hsieh, Inderjit S. Dhillon, Sanjiv Kumar
Preserving In-Context Learning ability in Large Language Model Fine-tuning. CoRR (2022)
Shuo Yang, Yijun Dong, Rachel Ward, Inderjit S. Dhillon, Sujay Sanghavi, Qi Lei
Sample Efficiency of Data Augmentation Consistency Regularization. CoRR (2022)
Minhao Cheng, Qi Lei, Pin-Yu Chen, Inderjit S. Dhillon, Cho-Jui Hsieh
CAT: Customized Adversarial Training for Improved Robustness. IJCAI (2022)
Patrick H. Chen, Wei-Cheng Chang, Hsiang-Fu Yu, Inderjit S. Dhillon, Cho-Jui Hsieh
FINGER: Fast Inference for Graph-based Approximate Nearest Neighbor Search. CoRR (2022)
Nilesh Gupta, Patrick H. Chen, Hsiang-Fu Yu, Cho-Jui Hsieh, Inderjit S. Dhillon
ELIAS: End-to-End Learning to Index and Search in Large Output Spaces. NeurIPS (2022)
Haoya Li, Hsiang-Fu Yu, Lexing Ying, Inderjit S. Dhillon
Accelerating Primal-dual Methods for Regularized Markov Decision Processes. CoRR (2022)
Nilesh Gupta, Patrick H. Chen, Hsiang-Fu Yu, Cho-Jui Hsieh, Inderjit S. Dhillon
End-to-End Learning to Index and Search in Large Output Spaces. CoRR (2022)
Anish Acharya, Sujay Sanghavi, Li Jing, Bhargav Bhushanam, Dhruv Choudhary, Michael Rabbat, Inderjit S. Dhillon
Positive Unlabeled Contrastive Learning. CoRR (2022)
Adam Block, Rahul Kidambi, Daniel N. Hill, Thorsten Joachims, Inderjit S. Dhillon
Counterfactual Learning To Rank for Utility-Maximizing Query Autocompletion. SIGIR (2022)
Shuo Yang, Tongzheng Ren, Sanjay Shakkottai, Eric Price, Inderjit S. Dhillon, Sujay Sanghavi
Linear Bandit Algorithms with Sublinear Time Complexity. ICML (2022)
Rudrajit Das, Anish Acharya, Abolfazl Hashemi, Sujay Sanghavi, Inderjit S. Dhillon, Ufuk Topcu
Faster non-convex federated learning via global and local momentum. UAI (2022)
Jiong Zhang, Wei-Cheng Chang, Hsiang-Fu Yu, Inderjit S. Dhillon
Fast Multi-Resolution Transformer Fine-tuning for Extreme Multi-label Text Classification. CoRR (2021)
Romain Lopez, Inderjit S. Dhillon, Michael I. Jordan
Learning from eXtreme Bandit Feedback. AAAI (2021)
Tavor Z. Baharav, Daniel L. Jiang, Kedarnath Kolluri, Sujay Sanghavi, Inderjit S. Dhillon
Enabling Efficiency-Precision Trade-offs for Label Trees in Extreme Classification. CoRR (2021)
Eli Chien, Wei-Cheng Chang, Cho-Jui Hsieh, Hsiang-Fu Yu, Jiong Zhang, Olgica Milenkovic, Inderjit S. Dhillon
Node Feature Extraction by Self-Supervised Multi-scale Neighborhood Prediction. CoRR (2021)
Haoya Li, Samarth Gupta, Hsiang-Fu Yu, Lexing Ying, Inderjit S. Dhillon
Quasi-Newton policy gradient algorithms. CoRR (2021)
Anish Acharya, Abolfazl Hashemi, Prateek Jain, Sujay Sanghavi, Inderjit S. Dhillon, Ufuk Topcu
Robust Training in High Dimensions via Block Coordinate Geometric Median Descent. CoRR (2021)
Wei-Cheng Chang, Daniel Jiang, Hsiang-Fu Yu, Choon-Hui Teo, Jiong Zhang, Kai Zhong, Kedarnath Kolluri, Qie Hu, Nikhil Shandilya, Vyacheslav Ievgrafov, Japinder Singh, Inderjit S. Dhillon
Extreme Multi-label Learning for Semantic Matching in Product Search. CoRR (2021)
Wei-Cheng Chang, Daniel Jiang, Hsiang-Fu Yu, Choon-Hui Teo, Jiong Zhang, Kai Zhong, Kedarnath Kolluri, Qie Hu, Nikhil Shandilya, Vyacheslav Ievgrafov, Japinder Singh, Inderjit S. Dhillon
Extreme Multi-label Learning for Semantic Matching in Product Search. KDD (2021)
Tavor Z. Baharav, Daniel L. Jiang, Kedarnath Kolluri, Sujay Sanghavi, Inderjit S. Dhillon
Enabling Efficiency-Precision Trade-offs for Label Trees in Extreme Classification. CIKM (2021)
Shuo Yang, Tongzheng Ren, Sanjay Shakkottai, Eric Price, Inderjit S. Dhillon, Sujay Sanghavi
Linear Bandit Algorithms with Sublinear Time Complexity. CoRR (2021)
Reese Pathak, Rajat Sen, Nikhil Rao, N. Benjamin Erichson, Michael I. Jordan, Inderjit S. Dhillon
Cluster-and-Conquer: A Framework For Time-Series Forecasting. CoRR (2021)
Shuo Yang, Tongzheng Ren, Inderjit S. Dhillon, Sujay Sanghavi
Combinatorial Bandits without Total Order for Arms. CoRR (2021)
Rudrajit Das, Abolfazl Hashemi, Sujay Sanghavi, Inderjit S. Dhillon
DP-NormFedAvg: Normalizing Client Updates for Privacy-Preserving Federated Learning. CoRR (2021)
Jiong Zhang, Wei-Cheng Chang, Hsiang-Fu Yu, Inderjit S. Dhillon
Fast Multi-Resolution Transformer Fine-tuning for Extreme Multi-label Text Classification. NeurIPS (2021)
Rajat Sen, Alexander Rakhlin, Lexing Ying, Rahul Kidambi, Dean P. Foster, Daniel N. Hill, Inderjit S. Dhillon
Top-k eXtreme Contextual Bandits with Arm Hierarchy. CoRR (2021)
Rajat Sen, Alexander Rakhlin, Lexing Ying, Rahul Kidambi, Dean Foster, Daniel N. Hill, Inderjit S. Dhillon
Top-k eXtreme Contextual Bandits with Arm Hierarchy. ICML (2021)
Philip A. Etter, Kai Zhong, Hsiang-Fu Yu, Lexing Ying, Inderjit S. Dhillon
Accelerating Inference for Sparse Extreme Multi-Label Ranking Trees. CoRR (2021)
Nishant Yadav, Rajat Sen, Daniel N. Hill, Arya Mazumdar, Inderjit S. Dhillon
Session-Aware Query Auto-completion using Extreme Multi-Label Ranking. KDD (2021)
Xuanqing Liu, Wei-Cheng Chang, Hsiang-Fu Yu, Cho-Jui Hsieh, Inderjit S. Dhillon
Label Disentanglement in Partition-based Extreme Multilabel Classification. NeurIPS (2021)
Yuanhao Xiong, Wei-Cheng Chang, Cho-Jui Hsieh, Hsiang-Fu Yu, Inderjit S. Dhillon
Extreme Zero-Shot Learning for Extreme Text Classification. CoRR (2021)
Xuanqing Liu, Wei-Cheng Chang, Hsiang-Fu Yu, Cho-Jui Hsieh, Inderjit S. Dhillon
Label Disentanglement in Partition-based Extreme Multilabel Classification. CoRR (2021)
Patrick H. Chen, Hsiang-Fu Yu, Inderjit S. Dhillon, Cho-Jui Hsieh
DRONE: Data-aware Low-rank Compression for Large NLP Models. NeurIPS (2021)
Rudrajit Das, Abolfazl Hashemi, Sujay Sanghavi, Inderjit S. Dhillon
Improved Convergence Rates for Non-Convex Federated Learning with Compression. CoRR (2020)
Devvrit, Minhao Cheng, Cho-Jui Hsieh, Inderjit S. Dhillon
Voting based ensemble improves robustness of defensive models. CoRR (2020)
Xuanqing Liu, Hsiang-Fu Yu, Inderjit S. Dhillon, Cho-Jui Hsieh
Learning to Encode Position for Transformer with Continuous Dynamical Model. CoRR (2020)
Yanyao Shen, Hsiang-Fu Yu, Sujay Sanghavi, Inderjit S. Dhillon
Extreme Multi-label Classification from Aggregated Labels. ICML (2020)
Wei-Cheng Chang, Hsiang-Fu Yu, Kai Zhong, Yiming Yang, Inderjit S. Dhillon
Taming Pretrained Transformers for Extreme Multi-label Text Classification. KDD (2020)
Romain Lopez, Inderjit S. Dhillon, Michael I. Jordan
Learning from eXtreme Bandit Feedback. CoRR (2020)
Joyce Jiyoung Whang, Yeonsung Jung, Seonggoo Kang, Dongho Yoo, Inderjit S. Dhillon
Scalable Anti-TrustRank with Qualified Site-level Seeds for Link-based Web Spam Detection. WWW (Companion Volume) (2020)
Hsiang-Fu Yu, Kai Zhong, Inderjit S. Dhillon
PECOS: Prediction for Enormous and Correlated Output Spaces. CoRR (2020)
Nishant Yadav, Rajat Sen, Daniel N. Hill, Arya Mazumdar, Inderjit S. Dhillon
Session-Aware Query Auto-completion using Extreme Multi-label Ranking. CoRR (2020)
Minhao Cheng, Qi Lei, Pin-Yu Chen, Inderjit S. Dhillon, Cho-Jui Hsieh
CAT: Customized Adversarial Training for Improved Robustness. CoRR (2020)
Xuanqing Liu, Hsiang-Fu Yu, Inderjit S. Dhillon, Cho-Jui Hsieh
Learning to Encode Position for Transformer with Continuous Dynamical Model. ICML (2020)
Joyce Jiyoung Whang, Inderjit S. Dhillon
Non-Exhaustive, Overlapping Co-Clustering: An Extended Analysis. CoRR (2020)
Abolfazl Hashemi, Anish Acharya, Rudrajit Das, Haris Vikalo, Sujay Sanghavi, Inderjit S. Dhillon
On the Benefits of Multiple Gossip Steps in Communication-Constrained Decentralized Optimization. CoRR (2020)
Yanyao Shen, Hsiang-Fu Yu, Sujay Sanghavi, Inderjit S. Dhillon
Extreme Multi-label Classification from Aggregated Labels. CoRR (2020)
Kai Zhong, Zhao Song, Prateek Jain, Inderjit S. Dhillon
Provable Non-linear Inductive Matrix Completion. NeurIPS (2019)
Qi Lei, Jiacheng Zhuo, Constantine Caramanis, Inderjit S. Dhillon, Alexandros G. Dimakis
Primal-Dual Block Frank-Wolfe. CoRR (2019)
Joyce Jiyoung Whang, Yangyang Hou, David F. Gleich, Inderjit S. Dhillon
Non-Exhaustive, Overlapping Clustering. IEEE Trans. Pattern Anal. Mach. Intell. 41 (11) (2019)
Qi Lei, Lingfei Wu, Pin-Yu Chen, Alex Dimakis, Inderjit S. Dhillon, Michael J. Witbrock
Discrete Adversarial Attacks and Submodular Optimization with Applications to Text Classification. MLSys (2019)
Qi Lei, Ajil Jalal, Inderjit S. Dhillon, Alexandros G. Dimakis
Inverting Deep Generative models, One layer at a time. NeurIPS (2019)
Anish Acharya, Rahul Goel, Angeliki Metallinou, Inderjit S. Dhillon
Online Embedding Compression for Text Classification Using Low Rank Matrix Factorization. AAAI (2019)
Jiong Zhang, Parameswaran Raman, Shihao Ji, Hsiang-Fu Yu, S. V. N. Vishwanathan, Inderjit S. Dhillon
Extreme Stochastic Variational Inference: Distributed Inference for Large Scale Mixture Models. AISTATS (2019)
Qi Lei, Jiacheng Zhuo, Constantine Caramanis, Inderjit S. Dhillon, Alexandros G. Dimakis
Primal-Dual Block Generalized Frank-Wolfe. NeurIPS (2019)
Inderjit S. Dhillon
Abstract of the Keynotes. IC3 (2019)
Rajat Sen, Hsiang-Fu Yu, Inderjit S. Dhillon
Think Globally, Act Locally: A Deep Neural Network Approach to High-Dimensional Time Series Forecasting. NeurIPS (2019)
Qi Lei, Jinfeng Yi, Roman Vaculín, Lingfei Wu, Inderjit S. Dhillon
Similarity Preserving Representation Learning for Time Series Clustering. IJCAI (2019)
Huan Zhang, Hongge Chen, Zhao Song, Duane S. Boning, Inderjit S. Dhillon, Cho-Jui Hsieh
The Limitations of Adversarial Training and the Blind-Spot Attack. CoRR (2019)
Qi Lei, Ajil Jalal, Inderjit S. Dhillon, Alexandros G. Dimakis
Inverting Deep Generative models, One layer at a time. CoRR (2019)
Huan Zhang, Hongge Chen, Zhao Song, Duane S. Boning, Inderjit S. Dhillon, Cho-Jui Hsieh
The Limitations of Adversarial Training and the Blind-Spot Attack. ICLR (Poster) (2019)
Wei-Cheng Chang, Hsiang-Fu Yu, Kai Zhong, Yiming Yang, Inderjit S. Dhillon
A Modular Deep Learning Approach for Extreme Multi-label Text Classification. CoRR (2019)
Rajat Sen, Hsiang-Fu Yu, Inderjit S. Dhillon
Think Globally, Act Locally: A Deep Neural Network Approach to High-Dimensional Time Series Forecasting. CoRR (2019)
Jiong Zhang, Hsiang-Fu Yu, Inderjit S. Dhillon
AutoAssist: A Framework to Accelerate Training of Deep Neural Networks. CoRR (2019)
Hsiang-Fu Yu, Cho-Jui Hsieh, Inderjit S. Dhillon
Parallel Asynchronous Stochastic Coordinate Descent with Auxiliary Variables. AISTATS (2019)
Jiong Zhang, Hsiang-Fu Yu, Inderjit S. Dhillon
AutoAssist: A Framework to Accelerate Training of Deep Neural Networks. NeurIPS (2019)
Vikas K. Garg, Inderjit S. Dhillon, Hsiang-Fu Yu
Multiresolution Transformer Networks: Recurrence is Not Essential for Modeling Hierarchical Structure. CoRR (2019)
Alexander Ratner, Dan Alistarh, Gustavo Alonso, David G. Andersen, Peter Bailis, Sarah Bird, Nicholas Carlini, Bryan Catanzaro, Eric Chung, Bill Dally, Jeff Dean, Inderjit S. Dhillon, Alexandros G. Dimakis, Pradeep Dubey, Charles Elkan, Grigori Fursin, Gregory R. Ganger, Lise Getoor, Phillip B. Gibbons, Garth A. Gibson, Joseph E. Gonzalez, Justin Gottschlich, Song Han, Kim M. Hazelwood, Furong Huang, Martin Jaggi, Kevin G. Jamieson, Michael I. Jordan, Gauri Joshi, Rania Khalaf, Jason Knight, Jakub Konecný, Tim Kraska, Arun Kumar, Anastasios Kyrillidis, Jing Li, Samuel Madden, H. Brendan McMahan, Erik Meijer, Ioannis Mitliagkas, Rajat Monga, Derek Gordon Murray, Dimitris S. Papailiopoulos, Gennady Pekhimenko, Theodoros Rekatsinas, Afshin Rostamizadeh, Christopher Ré, Christopher De Sa, Hanie Sedghi, Siddhartha Sen, Virginia Smith, Alex Smola, Dawn Song, Evan R. Sparks, Ion Stoica, Vivienne Sze, Madeleine Udell, Joaquin Vanschoren, Shivaram Venkataraman, Rashmi Vinayak, Markus Weimer, Andrew Gordon Wilson, Eric P. Xing, Matei Zaharia, Ce Zhang, Ameet Talwalkar
SysML: The New Frontier of Machine Learning Systems. CoRR (2019)
Tsui-Wei Weng, Huan Zhang, Hongge Chen, Zhao Song, Cho-Jui Hsieh, Duane S. Boning, Inderjit S. Dhillon, Luca Daniel
Towards Fast Computation of Certified Robustness for ReLU Networks. CoRR (2018)
Jiong Zhang, Yibo Lin, Zhao Song, Inderjit S. Dhillon
Learning Long Term Dependencies via Fourier Recurrent Units. ICML (2018)
Kai Zhong, Zhao Song, Prateek Jain, Inderjit S. Dhillon
Nonlinear Inductive Matrix Completion based on One-layer Neural Networks. CoRR (2018)
Anish Acharya, Rahul Goel, Angeliki Metallinou, Inderjit S. Dhillon
Online Embedding Compression for Text Classification using Low Rank Matrix Factorization. CoRR (2018)
Jiong Zhang, Qi Lei, Inderjit S. Dhillon
Stabilizing Gradients for Deep Neural Networks via Efficient SVD Parameterization. CoRR (2018)

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Publication Activity (10 Years)

Top Topics

Top Venues

Inderjit S. Dhillon