Inderjit S. Dhillon

321 papers A* 91A 28B 1Misc 1Journal 142Unranked 55

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Best of Both Worlds: Multimodal Reasoning and Generation via Unified Discrete Flow Matching. CoRR Onkar Susladkar, Tushar Prakash, Gayatri Deshmukh, Kiet A. Nguyen, Jiaxun Zhang, Adheesh Sunil Juvekar, Tianshu Bao, Lin Chai, Sparsh Mittal, Inderjit S. Dhillon, Ismini Lourentzou
2026	J	`jnl`	Interleaved Head Attention. CoRR Sai Surya Duvvuri, Chanakya Ekbote, Rachit Bansal, Rishabh Tiwari, Devvrit Khatri, David Brandfonbrener, Paul Pu Liang, Inderjit S. Dhillon, Manzil Zaheer
2026	J	`jnl`	LUCID: Attention with Preconditioned Representations. CoRR Sai Surya Duvvuri, Nirmal Patel, Nilesh Gupta, Inderjit S. Dhillon
2026	J	`jnl`	PyraTok: Language-Aligned Pyramidal Tokenizer for Video Understanding and Generation. CoRR Onkar Susladkar, Tushar Prakash, Adheesh Sunil Juvekar, Kiet A. Nguyen, Dong-Hwan Jang, Inderjit S. Dhillon, Ismini Lourentzou
2025	J	`jnl`	Compressing Many-Shots in In-Context Learning. CoRR Devvrit Khatri, Pranamya Kulkarni, Nilesh Gupta, Yerram Varun, Liqian Peng, Jay Yagnik, Praneeth Netrapalli, Cho-Jui Hsieh, Alec Go, Inderjit S. Dhillon, Aditya Kusupati, Prateek Jain
2025	A*	`conf`	Geometric Median (GM) Matching for Robust k-Subset Selection from Noisy Data. ICML Anish Acharya, Sujay Sanghavi, Alex Dimakis, Inderjit S. Dhillon
2025	J	`jnl`	Geometric Median Matching for Robust k-Subset Selection from Noisy Data. CoRR Anish Acharya, Sujay Sanghavi, Alexandros G. Dimakis, Inderjit S. Dhillon
2025	A*	`conf`	LASER: Attention with Exponential Transformation. ICML Sai Surya Duvvuri, Inderjit S. Dhillon
2025	J	`jnl`	LLM-guided Hierarchical Retrieval. CoRR Nilesh Gupta, Wei-Cheng Chang, Ngot Bui, Cho-Jui Hsieh, Inderjit S. Dhillon
2025	A*	`conf`	Large Language Models are Interpretable Learners. ICLR Ruochen Wang, Si Si, Felix X. Yu, Dorothea Wiesmann Rothuizen, Cho-Jui Hsieh, Inderjit S. Dhillon
2025	A*	`conf`	LoRA Done RITE: Robust Invariant Transformation Equilibration for LoRA Optimization. ICLR Jui-Nan Yen, Si Si, Zhao Meng, Felix X. Yu, Sai Surya Duvvuri, Inderjit S. Dhillon, Cho-Jui Hsieh, Sanjiv Kumar
2025	—	`conf`	Matryoshka Model Learning for Improved Elastic Student Models. KDD (2) Chetan Verma, Aditya Srinivas Timmaraju, Cho-Jui Hsieh, Suyash Damle, Ngot Bui, Yang Zhang, Wen Chen, Xin Liu, Prateek Jain, Inderjit S. Dhillon
2025	J	`jnl`	Matryoshka Model Learning for Improved Elastic Student Models. CoRR Chetan Verma, Aditya Srinivas Timmaraju, Cho-Jui Hsieh, Suyash Damle, Ngot Bui, Yang Zhang, Wen Chen, Xin Liu, Prateek Jain, Inderjit S. Dhillon
2025	A*	`conf`	Retraining with Predicted Hard Labels Provably Increases Model Accuracy. ICML Rudrajit Das, Inderjit S. Dhillon, Alessandro Epasto, Adel Javanmard, Jieming Mao, Vahab Mirrokni, Sujay Sanghavi, Peilin Zhong
2025	J	`jnl`	Scalable In-context Ranking with Generative Models. CoRR Nilesh Gupta, Chong You, Srinadh Bhojanapalli, Sanjiv Kumar, Inderjit S. Dhillon, Felix X. Yu
2025	J	`jnl`	The Art of Scaling Reinforcement Learning Compute for LLMs. CoRR Devvrit Khatri, Lovish Madaan, Rishabh Tiwari, Rachit Bansal, Sai Surya Duvvuri, Manzil Zaheer, Inderjit S. Dhillon, David Brandfonbrener, Rishabh Agarwal
2024	J	`jnl`	Accelerating Primal-Dual Methods for Regularized Markov Decision Processes. SIAM J. Optim. Haoya Li, Hsiang-Fu Yu, Lexing Ying, Inderjit S. Dhillon
2024	—	`conf`	Automatic Engineering of Long Prompts. ACL (Findings) Cho-Jui Hsieh, Si Si, Felix X. Yu, Inderjit S. Dhillon
2024	A*	`conf`	Combining Axes Preconditioners through Kronecker Approximation for Deep Learning. ICLR Sai Surya Duvvuri, Devvrit, Rohan Anil, Cho-Jui Hsieh, Inderjit S. Dhillon
2024	A*	`conf`	Dual-Encoders for Extreme Multi-label Classification. ICLR Nilesh Gupta, Devvrit, Ankit Singh Rawat, Srinadh Bhojanapalli, Prateek Jain, Inderjit S. Dhillon
2024	J	`jnl`	EHI: End-to-end Learning of Hierarchical Index for Efficient Dense Retrieval. Trans. Mach. Learn. Res. Ramnath Kumar, Anshul Mittal, Nilesh Gupta, Aditya Kusupati, Inderjit S. Dhillon, Prateek Jain
2024	J	`jnl`	Geometric Median (GM) Matching for Robust Data Pruning. CoRR Anish Acharya, Inderjit S. Dhillon, Sujay Sanghavi
2024	J	`jnl`	LASER: Attention with Exponential Transformation. CoRR Sai Surya Duvvuri, Inderjit S. Dhillon
2024	J	`jnl`	Large Language Models are Interpretable Learners. CoRR Ruochen Wang, Si Si, Felix X. Yu, Dorothea Wiesmann, Cho-Jui Hsieh, Inderjit S. Dhillon
2024	J	`jnl`	LoRA Done RITE: Robust Invariant Transformation Equilibration for LoRA Optimization. CoRR Jui-Nan Yen, Si Si, Zhao Meng, Felix X. Yu, Sai Surya Duvvuri, Inderjit S. Dhillon, Cho-Jui Hsieh, Sanjiv Kumar
2024	A*	`conf`	MatFormer: Nested Transformer for Elastic Inference. NeurIPS Devvrit, Sneha Kudugunta, Aditya Kusupati, Tim Dettmers, Kaifeng Chen, Inderjit S. Dhillon, Yulia Tsvetkov, Hanna Hajishirzi, Sham M. Kakade, Ali Farhadi, Prateek Jain
2024	—	`conf`	PRISM: A New Lens for Improved Color Understanding. EMNLP (Industry Track) Arjun R. Akula, Garima Pruthi, Inderjit S. Dhillon, Pradyumna Narayana, Sugato Basu, Varun Jampani
2024	J	`jnl`	Retraining with Predicted Hard Labels Provably Increases Model Accuracy. CoRR Rudrajit Das, Inderjit S. Dhillon, Alessandro Epasto, Adel Javanmard, Jieming Mao, Vahab Mirrokni, Sujay Sanghavi, Peilin Zhong
2024	J	`jnl`	Towards Quantifying the Preconditioning Effect of Adam. CoRR Rudrajit Das, Naman Agarwal, Sujay Sanghavi, Inderjit S. Dhillon
2024	A*	`conf`	Two-stage LLM Fine-tuning with Less Specialization and More Generalization. ICLR Yihan Wang, Si Si, Daliang Li, Michal Lukasik, Felix X. Yu, Cho-Jui Hsieh, Inderjit S. Dhillon, Sanjiv Kumar
2023	A*	`conf`	A Computationally Efficient Sparsified Online Newton Method. NeurIPS Devvrit, Sai Surya Duvvuri, Rohan Anil, Vineet Gupta, Cho-Jui Hsieh, Inderjit S. Dhillon
2023	J	`jnl`	A Computationally Efficient Sparsified Online Newton Method. CoRR Devvrit, Sai Surya Duvvuri, Rohan Anil, Vineet Gupta, Cho-Jui Hsieh, Inderjit S. Dhillon
2023	J	`jnl`	Approximate Newton Policy Gradient Algorithms. SIAM J. Sci. Comput. Haoya Li, Samarth Gupta, Hsiang-Fu Yu, Lexing Ying, Inderjit S. Dhillon
2023	J	`jnl`	Automatic Engineering of Long Prompts. CoRR Cho-Jui Hsieh, Si Si, Felix X. Yu, Inderjit S. Dhillon
2023	A*	`conf`	Block Low-Rank Preconditioner with Shared Basis for Stochastic Optimization. NeurIPS Jui-Nan Yen, Sai Surya Duvvuri, Inderjit S. Dhillon, Cho-Jui Hsieh
2023	J	`jnl`	EHI: End-to-end Learning of Hierarchical Index for Efficient Dense Retrieval. CoRR Ramnath Kumar, Anshul Mittal, Nilesh Gupta, Aditya Kusupati, Inderjit S. Dhillon, Prateek Jain
2023	J	`jnl`	Efficacy of Dual-Encoders for Extreme Multi-Label Classification. CoRR Nilesh Gupta, Devvrit Khatri, Ankit Singh Rawat, Srinadh Bhojanapalli, Prateek Jain, Inderjit S. Dhillon
2023	A*	`conf`	FINGER: Fast Inference for Graph-based Approximate Nearest Neighbor Search. WWW Patrick H. Chen, Wei-Cheng Chang, Jyun-Yu Jiang, Hsiang-Fu Yu, Inderjit S. Dhillon, Cho-Jui Hsieh
2023	J	`jnl`	MatFormer: Nested Transformer for Elastic Inference. CoRR Devvrit, Sneha Kudugunta, Aditya Kusupati, Tim Dettmers, Kaifeng Chen, Inderjit S. Dhillon, Yulia Tsvetkov, Hannaneh Hajishirzi, Sham M. Kakade, Ali Farhadi, Prateek Jain
2023	A	`conf`	Sample Efficiency of Data Augmentation Consistency Regularization. AISTATS Shuo Yang, Yijun Dong, Rachel A. Ward, Inderjit S. Dhillon, Sujay Sanghavi, Qi Lei
2022	J	`jnl`	Accelerating Primal-dual Methods for Regularized Markov Decision Processes. CoRR Haoya Li, Hsiang-Fu Yu, Lexing Ying, Inderjit S. Dhillon
2022	A*	`conf`	CAT: Customized Adversarial Training for Improved Robustness. IJCAI Minhao Cheng, Qi Lei, Pin-Yu Chen, Inderjit S. Dhillon, Cho-Jui Hsieh
2022	A*	`conf`	Counterfactual Learning To Rank for Utility-Maximizing Query Autocompletion. SIGIR Adam Block, Rahul Kidambi, Daniel N. Hill, Thorsten Joachims, Inderjit S. Dhillon
2022	J	`jnl`	Counterfactual Learning To Rank for Utility-Maximizing Query Autocompletion. CoRR Adam Block, Rahul Kidambi, Daniel N. Hill, Thorsten Joachims, Inderjit S. Dhillon
2022	A*	`conf`	ELIAS: End-to-End Learning to Index and Search in Large Output Spaces. NeurIPS Nilesh Gupta, Patrick H. Chen, Hsiang-Fu Yu, Cho-Jui Hsieh, Inderjit S. Dhillon
2022	J	`jnl`	End-to-End Learning to Index and Search in Large Output Spaces. CoRR Nilesh Gupta, Patrick H. Chen, Hsiang-Fu Yu, Cho-Jui Hsieh, Inderjit S. Dhillon
2022	A*	`conf`	Enterprise-Scale Search: Accelerating Inference for Sparse Extreme Multi-Label Ranking Trees. WWW Philip A. Etter, Kai Zhong, Hsiang-Fu Yu, Lexing Ying, Inderjit S. Dhillon
2022	—	`conf`	Extreme Zero-Shot Learning for Extreme Text Classification. NAACL-HLT Yuanhao Xiong, Wei-Cheng Chang, Cho-Jui Hsieh, Hsiang-Fu Yu, Inderjit S. Dhillon
2022	J	`jnl`	FINGER: Fast Inference for Graph-based Approximate Nearest Neighbor Search. CoRR Patrick H. Chen, Wei-Cheng Chang, Hsiang-Fu Yu, Inderjit S. Dhillon, Cho-Jui Hsieh
2022	A	`conf`	Faster non-convex federated learning via global and local momentum. UAI Rudrajit Das, Anish Acharya, Abolfazl Hashemi, Sujay Sanghavi, Inderjit S. Dhillon, Ufuk Topcu
2022	A*	`conf`	Linear Bandit Algorithms with Sublinear Time Complexity. ICML Shuo Yang, Tongzheng Ren, Sanjay Shakkottai, Eric Price, Inderjit S. Dhillon, Sujay Sanghavi
2022	A*	`conf`	Node Feature Extraction by Self-Supervised Multi-scale Neighborhood Prediction. ICLR Eli Chien, Wei-Cheng Chang, Cho-Jui Hsieh, Hsiang-Fu Yu, Jiong Zhang, Olgica Milenkovic, Inderjit S. Dhillon
2022	J	`jnl`	On the Benefits of Multiple Gossip Steps in Communication-Constrained Decentralized Federated Learning. IEEE Trans. Parallel Distributed Syst. Abolfazl Hashemi, Anish Acharya, Rudrajit Das, Haris Vikalo, Sujay Sanghavi, Inderjit S. Dhillon
2022	J	`jnl`	PECOS: Prediction for Enormous and Correlated Output Spaces. J. Mach. Learn. Res. Hsiang-Fu Yu, Kai Zhong, Jiong Zhang, Wei-Cheng Chang, Inderjit S. Dhillon
2022	J	`jnl`	Positive Unlabeled Contrastive Learning. CoRR Anish Acharya, Sujay Sanghavi, Li Jing, Bhargav Bhushanam, Dhruv Choudhary, Michael G. Rabbat, Inderjit S. Dhillon
2022	J	`jnl`	Preserving In-Context Learning ability in Large Language Model Fine-tuning. CoRR Yihan Wang, Si Si, Daliang Li, Michal Lukasik, Felix X. Yu, Cho-Jui Hsieh, Inderjit S. Dhillon, Sanjiv Kumar
2022	A	`conf`	Robust Training in High Dimensions via Block Coordinate Geometric Median Descent. AISTATS Anish Acharya, Abolfazl Hashemi, Prateek Jain, Sujay Sanghavi, Inderjit S. Dhillon, Ufuk Topcu
2022	A*	`conf`	S3GC: Scalable Self-Supervised Graph Clustering. NeurIPS Devvrit, Aditya Sinha, Inderjit S. Dhillon, Prateek Jain
2022	J	`jnl`	Sample Efficiency of Data Augmentation Consistency Regularization. CoRR Shuo Yang, Yijun Dong, Rachel A. Ward, Inderjit S. Dhillon, Sujay Sanghavi, Qi Lei
2021	J	`jnl`	Accelerating Inference for Sparse Extreme Multi-Label Ranking Trees. CoRR Philip A. Etter, Kai Zhong, Hsiang-Fu Yu, Lexing Ying, Inderjit S. Dhillon
2021	J	`jnl`	Cluster-and-Conquer: A Framework For Time-Series Forecasting. CoRR Reese Pathak, Rajat Sen, Nikhil Rao, N. Benjamin Erichson, Michael I. Jordan, Inderjit S. Dhillon
2021	J	`jnl`	Combinatorial Bandits without Total Order for Arms. CoRR Shuo Yang, Tongzheng Ren, Inderjit S. Dhillon, Sujay Sanghavi
2021	J	`jnl`	DP-NormFedAvg: Normalizing Client Updates for Privacy-Preserving Federated Learning. CoRR Rudrajit Das, Abolfazl Hashemi, Sujay Sanghavi, Inderjit S. Dhillon
2021	A*	`conf`	DRONE: Data-aware Low-rank Compression for Large NLP Models. NeurIPS Patrick H. Chen, Hsiang-Fu Yu, Inderjit S. Dhillon, Cho-Jui Hsieh
2021	A	`conf`	Enabling Efficiency-Precision Trade-offs for Label Trees in Extreme Classification. CIKM Tavor Z. Baharav, Daniel L. Jiang, Kedarnath Kolluri, Sujay Sanghavi, Inderjit S. Dhillon
2021	J	`jnl`	Enabling Efficiency-Precision Trade-offs for Label Trees in Extreme Classification. CoRR Tavor Z. Baharav, Daniel L. Jiang, Kedarnath Kolluri, Sujay Sanghavi, Inderjit S. Dhillon
2021	A*	`conf`	Extreme Multi-label Learning for Semantic Matching in Product Search. KDD 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
2021	J	`jnl`	Extreme Multi-label Learning for Semantic Matching in Product Search. CoRR 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
2021	J	`jnl`	Extreme Zero-Shot Learning for Extreme Text Classification. CoRR Yuanhao Xiong, Wei-Cheng Chang, Cho-Jui Hsieh, Hsiang-Fu Yu, Inderjit S. Dhillon
2021	A*	`conf`	Fast Multi-Resolution Transformer Fine-tuning for Extreme Multi-label Text Classification. NeurIPS Jiong Zhang, Wei-Cheng Chang, Hsiang-Fu Yu, Inderjit S. Dhillon
2021	J	`jnl`	Fast Multi-Resolution Transformer Fine-tuning for Extreme Multi-label Text Classification. CoRR Jiong Zhang, Wei-Cheng Chang, Hsiang-Fu Yu, Inderjit S. Dhillon
2021	A*	`conf`	Label Disentanglement in Partition-based Extreme Multilabel Classification. NeurIPS Xuanqing Liu, Wei-Cheng Chang, Hsiang-Fu Yu, Cho-Jui Hsieh, Inderjit S. Dhillon
2021	J	`jnl`	Label Disentanglement in Partition-based Extreme Multilabel Classification. CoRR Xuanqing Liu, Wei-Cheng Chang, Hsiang-Fu Yu, Cho-Jui Hsieh, Inderjit S. Dhillon
2021	A*	`conf`	Learning from eXtreme Bandit Feedback. AAAI Romain Lopez, Inderjit S. Dhillon, Michael I. Jordan
2021	J	`jnl`	Linear Bandit Algorithms with Sublinear Time Complexity. CoRR Shuo Yang, Tongzheng Ren, Sanjay Shakkottai, Eric Price, Inderjit S. Dhillon, Sujay Sanghavi
2021	J	`jnl`	Node Feature Extraction by Self-Supervised Multi-scale Neighborhood Prediction. CoRR Eli Chien, Wei-Cheng Chang, Cho-Jui Hsieh, Hsiang-Fu Yu, Jiong Zhang, Olgica Milenkovic, Inderjit S. Dhillon
2021	J	`jnl`	Quasi-Newton policy gradient algorithms. CoRR Haoya Li, Samarth Gupta, Hsiang-Fu Yu, Lexing Ying, Inderjit S. Dhillon
2021	J	`jnl`	Robust Training in High Dimensions via Block Coordinate Geometric Median Descent. CoRR Anish Acharya, Abolfazl Hashemi, Prateek Jain, Sujay Sanghavi, Inderjit S. Dhillon, Ufuk Topcu
2021	A*	`conf`	Session-Aware Query Auto-completion using Extreme Multi-Label Ranking. KDD Nishant Yadav, Rajat Sen, Daniel N. Hill, Arya Mazumdar, Inderjit S. Dhillon
2021	A*	`conf`	Top-k eXtreme Contextual Bandits with Arm Hierarchy. ICML Rajat Sen, Alexander Rakhlin, Lexing Ying, Rahul Kidambi, Dean P. Foster, Daniel N. Hill, Inderjit S. Dhillon
2021	J	`jnl`	Top-k eXtreme Contextual Bandits with Arm Hierarchy. CoRR Rajat Sen, Alexander Rakhlin, Lexing Ying, Rahul Kidambi, Dean P. Foster, Daniel N. Hill, Inderjit S. Dhillon
2020	J	`jnl`	CAT: Customized Adversarial Training for Improved Robustness. CoRR Minhao Cheng, Qi Lei, Pin-Yu Chen, Inderjit S. Dhillon, Cho-Jui Hsieh
2020	A*	`conf`	Extreme Multi-label Classification from Aggregated Labels. ICML Yanyao Shen, Hsiang-Fu Yu, Sujay Sanghavi, Inderjit S. Dhillon
2020	J	`jnl`	Extreme Multi-label Classification from Aggregated Labels. CoRR Yanyao Shen, Hsiang-Fu Yu, Sujay Sanghavi, Inderjit S. Dhillon
2020	J	`jnl`	Improved Convergence Rates for Non-Convex Federated Learning with Compression. CoRR Rudrajit Das, Abolfazl Hashemi, Sujay Sanghavi, Inderjit S. Dhillon
2020	J	`jnl`	Learning from eXtreme Bandit Feedback. CoRR Romain Lopez, Inderjit S. Dhillon, Michael I. Jordan
2020	A*	`conf`	Learning to Encode Position for Transformer with Continuous Dynamical Model. ICML Xuanqing Liu, Hsiang-Fu Yu, Inderjit S. Dhillon, Cho-Jui Hsieh
2020	J	`jnl`	Learning to Encode Position for Transformer with Continuous Dynamical Model. CoRR Xuanqing Liu, Hsiang-Fu Yu, Inderjit S. Dhillon, Cho-Jui Hsieh
2020	J	`jnl`	Non-Exhaustive, Overlapping Co-Clustering: An Extended Analysis. CoRR Joyce Jiyoung Whang, Inderjit S. Dhillon
2020	J	`jnl`	On the Benefits of Multiple Gossip Steps in Communication-Constrained Decentralized Optimization. CoRR Abolfazl Hashemi, Anish Acharya, Rudrajit Das, Haris Vikalo, Sujay Sanghavi, Inderjit S. Dhillon
2020	J	`jnl`	PECOS: Prediction for Enormous and Correlated Output Spaces. CoRR Hsiang-Fu Yu, Kai Zhong, Inderjit S. Dhillon
2020	—	`ed.`	Proceedings of the Third Conference on Machine Learning and Systems, MLSys 2020, Austin, TX, USA, March 2-4, 2020 MLSys Inderjit S. Dhillon, Dimitris S. Papailiopoulos, Vivienne Sze
2020	—	`conf`	Scalable Anti-TrustRank with Qualified Site-level Seeds for Link-based Web Spam Detection. WWW (Companion Volume) Joyce Jiyoung Whang, Yeonsung Jung, Seonggoo Kang, Dongho Yoo, Inderjit S. Dhillon
2020	J	`jnl`	Session-Aware Query Auto-completion using Extreme Multi-label Ranking. CoRR Nishant Yadav, Rajat Sen, Daniel N. Hill, Arya Mazumdar, Inderjit S. Dhillon
2020	A*	`conf`	Taming Pretrained Transformers for Extreme Multi-label Text Classification. KDD Wei-Cheng Chang, Hsiang-Fu Yu, Kai Zhong, Yiming Yang, Inderjit S. Dhillon
2020	J	`jnl`	Voting based ensemble improves robustness of defensive models. CoRR Devvrit, Minhao Cheng, Cho-Jui Hsieh, Inderjit S. Dhillon
2019	J	`jnl`	A Modular Deep Learning Approach for Extreme Multi-label Text Classification. CoRR Wei-Cheng Chang, Hsiang-Fu Yu, Kai Zhong, Yiming Yang, Inderjit S. Dhillon
2019	—	`conf`	Abstract of the Keynotes. IC3 Inderjit S. Dhillon
2019	A*	`conf`	AutoAssist: A Framework to Accelerate Training of Deep Neural Networks. NeurIPS Jiong Zhang, Hsiang-Fu Yu, Inderjit S. Dhillon
2019	J	`jnl`	AutoAssist: A Framework to Accelerate Training of Deep Neural Networks. CoRR Jiong Zhang, Hsiang-Fu Yu, Inderjit S. Dhillon
2019	—	`conf`	Discrete Adversarial Attacks and Submodular Optimization with Applications to Text Classification. SysML Qi Lei, Lingfei Wu, Pin-Yu Chen, Alex Dimakis, Inderjit S. Dhillon, Michael Witbrock
2019	A	`conf`	Extreme Stochastic Variational Inference: Distributed Inference for Large Scale Mixture Models. AISTATS Jiong Zhang, Parameswaran Raman, Shihao Ji, Hsiang-Fu Yu, S. V. N. Vishwanathan, Inderjit S. Dhillon
2019	A*	`conf`	Inverting Deep Generative models, One layer at a time. NeurIPS Qi Lei, Ajil Jalal, Inderjit S. Dhillon, Alexandros G. Dimakis
2019	J	`jnl`	Inverting Deep Generative models, One layer at a time. CoRR Qi Lei, Ajil Jalal, Inderjit S. Dhillon, Alexandros G. Dimakis
2019	J	`jnl`	Multiresolution Transformer Networks: Recurrence is Not Essential for Modeling Hierarchical Structure. CoRR Vikas K. Garg, Inderjit S. Dhillon, Hsiang-Fu Yu
2019	J	`jnl`	Non-Exhaustive, Overlapping Clustering. IEEE Trans. Pattern Anal. Mach. Intell. Joyce Jiyoung Whang, Yangyang Hou, David F. Gleich, Inderjit S. Dhillon
2019	A*	`conf`	Online Embedding Compression for Text Classification Using Low Rank Matrix Factorization. AAAI Anish Acharya, Rahul Goel, Angeliki Metallinou, Inderjit S. Dhillon
2019	A	`conf`	Parallel Asynchronous Stochastic Coordinate Descent with Auxiliary Variables. AISTATS Hsiang-Fu Yu, Cho-Jui Hsieh, Inderjit S. Dhillon
2019	J	`jnl`	Primal-Dual Block Frank-Wolfe. CoRR Qi Lei, Jiacheng Zhuo, Constantine Caramanis, Inderjit S. Dhillon, Alexandros G. Dimakis
2019	A*	`conf`	Primal-Dual Block Generalized Frank-Wolfe. NeurIPS Qi Lei, Jiacheng Zhuo, Constantine Caramanis, Inderjit S. Dhillon, Alexandros G. Dimakis
2019	A*	`conf`	Provable Non-linear Inductive Matrix Completion. NeurIPS Kai Zhong, Zhao Song, Prateek Jain, Inderjit S. Dhillon
2019	A*	`conf`	Similarity Preserving Representation Learning for Time Series Clustering. IJCAI Qi Lei, Jinfeng Yi, Roman Vaculín, Lingfei Wu, Inderjit S. Dhillon
2019	J	`jnl`	SysML: The New Frontier of Machine Learning Systems. CoRR 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, 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 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 Randall 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
2019	—	`conf`	The Limitations of Adversarial Training and the Blind-Spot Attack. ICLR (Poster) Huan Zhang, Hongge Chen, Zhao Song, Duane S. Boning, Inderjit S. Dhillon, Cho-Jui Hsieh
2019	J	`jnl`	The Limitations of Adversarial Training and the Blind-Spot Attack. CoRR Huan Zhang, Hongge Chen, Zhao Song, Duane S. Boning, Inderjit S. Dhillon, Cho-Jui Hsieh
2019	A*	`conf`	Think Globally, Act Locally: A Deep Neural Network Approach to High-Dimensional Time Series Forecasting. NeurIPS Rajat Sen, Hsiang-Fu Yu, Inderjit S. Dhillon
2019	J	`jnl`	Think Globally, Act Locally: A Deep Neural Network Approach to High-Dimensional Time Series Forecasting. CoRR Rajat Sen, Hsiang-Fu Yu, Inderjit S. Dhillon
2018	J	`jnl`	Discrete Attacks and Submodular Optimization with Applications to Text Classification. CoRR Qi Lei, Lingfei Wu, Pin-Yu Chen, Alexandros G. Dimakis, Inderjit S. Dhillon, Michael Witbrock
2018	A*	`conf`	Learning Long Term Dependencies via Fourier Recurrent Units. ICML Jiong Zhang, Yibo Lin, Zhao Song, Inderjit S. Dhillon
2018	J	`jnl`	Learning Long Term Dependencies via Fourier Recurrent Units. CoRR Jiong Zhang, Yibo Lin, Zhao Song, Inderjit S. Dhillon
2018	J	`jnl`	Nonlinear Inductive Matrix Completion based on One-layer Neural Networks. CoRR Kai Zhong, Zhao Song, Prateek Jain, Inderjit S. Dhillon
2018	J	`jnl`	Online Embedding Compression for Text Classification using Low Rank Matrix Factorization. CoRR Anish Acharya, Rahul Goel, Angeliki Metallinou, Inderjit S. Dhillon
2018	—	`conf`	Realtime Query Completion via Deep Language Models. eCOM@SIGIR Po-Wei Wang, Huan Zhang, Vijai Mohan, Inderjit S. Dhillon, J. Zico Kolter
2018	A*	`conf`	Stabilizing Gradients for Deep Neural Networks via Efficient SVD Parameterization. ICML Jiong Zhang, Qi Lei, Inderjit S. Dhillon
2018	J	`jnl`	Stabilizing Gradients for Deep Neural Networks via Efficient SVD Parameterization. CoRR Jiong Zhang, Qi Lei, Inderjit S. Dhillon
2018	A*	`conf`	Towards Fast Computation of Certified Robustness for ReLU Networks. ICML Tsui-Wei Weng, Huan Zhang, Hongge Chen, Zhao Song, Cho-Jui Hsieh, Luca Daniel, Duane S. Boning, Inderjit S. Dhillon
2018	J	`jnl`	Towards Fast Computation of Certified Robustness for ReLU Networks. CoRR Tsui-Wei Weng, Huan Zhang, Hongge Chen, Zhao Song, Cho-Jui Hsieh, Duane S. Boning, Inderjit S. Dhillon, Luca Daniel
2018	J	`jnl`	Using Side Information to Reliably Learn Low-Rank Matrices from Missing and Corrupted Observations. J. Mach. Learn. Res. Kai-Yang Chiang, Inderjit S. Dhillon, Cho-Jui Hsieh
2017	—	`conf`	A Greedy Approach for Budgeted Maximum Inner Product Search. NIPS Hsiang-Fu Yu, Cho-Jui Hsieh, Qi Lei, Inderjit S. Dhillon
2017	A*	`conf`	A Unified Algorithm for One-Cass Structured Matrix Factorization with Side Information. AAAI Hsiang-Fu Yu, Hsin-Yuan Huang, Inderjit S. Dhillon, Chih-Jen Lin
2017	A*	`conf`	Communication-Efficient Distributed Block Minimization for Nonlinear Kernel Machines. KDD Cho-Jui Hsieh, Si Si, Inderjit S. Dhillon
2017	J	`jnl`	Cost-Sensitive Learning with Noisy Labels. J. Mach. Learn. Res. Nagarajan Natarajan, Inderjit S. Dhillon, Pradeep Ravikumar, Ambuj Tewari
2017	A*	`conf`	Doubly Greedy Primal-Dual Coordinate Descent for Sparse Empirical Risk Minimization. ICML Qi Lei, Ian En-Hsu Yen, Chao-Yuan Wu, Inderjit S. Dhillon, Pradeep Ravikumar
2017	A	`conf`	Fast Classification with Binary Prototypes. AISTATS Kai Zhong, Ruiqi Guo, Sanjiv Kumar, Bowei Yan, David Simcha, Inderjit S. Dhillon
2017	A*	`conf`	Gradient Boosted Decision Trees for High Dimensional Sparse Output. ICML Si Si, Huan Zhang, S. Sathiya Keerthi, Dhruv Mahajan, Inderjit S. Dhillon, Cho-Jui Hsieh
2017	A	`conf`	Greedy Direction Method of Multiplier for MAP Inference of Large Output Domain. AISTATS Xiangru Huang, Ian En-Hsu Yen, Ruohan Zhang, Qixing Huang, Pradeep Ravikumar, Inderjit S. Dhillon
2017	J	`jnl`	Learning Non-overlapping Convolutional Neural Networks with Multiple Kernels. CoRR Kai Zhong, Zhao Song, Inderjit S. Dhillon
2017	J	`jnl`	Memory Efficient Kernel Approximation. J. Mach. Learn. Res. Si Si, Cho-Jui Hsieh, Inderjit S. Dhillon
2017	A	`conf`	Non-Exhaustive, Overlapping Co-Clustering. CIKM Joyce Jiyoung Whang, Inderjit S. Dhillon
2017	A*	`conf`	PPDsparse: A Parallel Primal-Dual Sparse Method for Extreme Classification. KDD Ian En-Hsu Yen, Xiangru Huang, Wei Dai, Pradeep Ravikumar, Inderjit S. Dhillon, Eric P. Xing
2017	J	`jnl`	Partial Hard Thresholding. IEEE Trans. Inf. Theory Prateek Jain, Ambuj Tewari, Inderjit S. Dhillon
2017	A	`conf`	Rank Aggregation and Prediction with Item Features. AISTATS Kai-Yang Chiang, Cho-Jui Hsieh, Inderjit S. Dhillon
2017	A*	`conf`	Recovery Guarantees for One-hidden-layer Neural Networks. ICML Kai Zhong, Zhao Song, Prateek Jain, Peter L. Bartlett, Inderjit S. Dhillon
2017	J	`jnl`	Recovery Guarantees for One-hidden-layer Neural Networks. CoRR Kai Zhong, Zhao Song, Prateek Jain, Peter L. Bartlett, Inderjit S. Dhillon
2017	A	`conf`	Scalable Convex Multiple Sequence Alignment via Entropy-Regularized Dual Decomposition. AISTATS Jiong Zhang, Ian En-Hsu Yen, Pradeep Ravikumar, Inderjit S. Dhillon
2017	J	`jnl`	Similarity Preserving Representation Learning for Time Series Analysis. CoRR Qi Lei, Jinfeng Yi, Roman Vaculín, Lingfei Wu, Inderjit S. Dhillon
2016	A*	`conf`	A Convex Atomic-Norm Approach to Multiple Sequence Alignment and Motif Discovery. ICML Ian En-Hsu Yen, Xin Lin, Jiong Zhang, Pradeep Ravikumar, Inderjit S. Dhillon
2016	J	`jnl`	A Greedy Approach for Budgeted Maximum Inner Product Search. CoRR Hsiang-Fu Yu, Cho-Jui Hsieh, Qi Lei, Inderjit S. Dhillon
2016	—	`conf`	Asynchronous Parallel Greedy Coordinate Descent. NIPS Yang You, Xiangru Lian, Ji Liu, Hsiang-Fu Yu, Inderjit S. Dhillon, James Demmel, Cho-Jui Hsieh
2016	J	`jnl`	Clustered Matrix Approximation. SIAM J. Matrix Anal. Appl. Berkant Savas, Inderjit S. Dhillon
2016	J	`jnl`	Communication-Efficient Parallel Block Minimization for Kernel Machines. CoRR Cho-Jui Hsieh, Si Si, Inderjit S. Dhillon
2016	A*	`conf`	Computationally Efficient Nyström Approximation using Fast Transforms. ICML Si Si, Cho-Jui Hsieh, Inderjit S. Dhillon
2016	—	`conf`	Coordinate-wise Power Method. NIPS Qi Lei, Kai Zhong, Inderjit S. Dhillon
2016	—	`conf`	Dual Decomposed Learning with Factorwise Oracle for Structural SVM of Large Output Domain. NIPS Ian En-Hsu Yen, Xiangru Huang, Kai Zhong, Ruohan Zhang, Pradeep Ravikumar, Inderjit S. Dhillon
2016	J	`jnl`	Efficient and Non-Convex Coordinate Descent for Symmetric Nonnegative Matrix Factorization. IEEE Trans. Signal Process. Arnaud Vandaele, Nicolas Gillis, Qi Lei, Kai Zhong, Inderjit S. Dhillon
2016	A	`conf`	Fast Multiplier Methods to Optimize Non-exhaustive, Overlapping Clustering. SDM Yangyang Hou, Joyce Jiyoung Whang, David F. Gleich, Inderjit S. Dhillon
2016	J	`jnl`	Fast Multiplier Methods to Optimize Non-exhaustive, Overlapping Clustering. CoRR Yangyang Hou, Joyce Jiyoung Whang, David F. Gleich, Inderjit S. Dhillon
2016	A*	`conf`	Goal-Directed Inductive Matrix Completion. KDD Si Si, Kai-Yang Chiang, Cho-Jui Hsieh, Nikhil Rao, Inderjit S. Dhillon
2016	J	`jnl`	Kernel Ridge Regression via Partitioning. CoRR Rashish Tandon, Si Si, Pradeep Ravikumar, Inderjit S. Dhillon
2016	—	`conf`	Mixed Linear Regression with Multiple Components. NIPS Kai Zhong, Prateek Jain, Inderjit S. Dhillon
2016	J	`jnl`	Nomadic Computing for Big Data Analytics. Computer Hsiang-Fu Yu, Cho-Jui Hsieh, Hyokun Yun, S. V. N. Vishwanathan, Inderjit S. Dhillon
2016	A*	`conf`	Optimal Classification with Multivariate Losses. ICML Nagarajan Natarajan, Oluwasanmi Koyejo, Pradeep Ravikumar, Inderjit S. Dhillon
2016	J	`jnl`	Overlapping Community Detection Using Neighborhood-Inflated Seed Expansion. IEEE Trans. Knowl. Data Eng. Joyce Jiyoung Whang, David F. Gleich, Inderjit S. Dhillon
2016	A*	`conf`	PD-Sparse : A Primal and Dual Sparse Approach to Extreme Multiclass and Multilabel Classification. ICML Ian En-Hsu Yen, Xiangru Huang, Pradeep Ravikumar, Kai Zhong, Inderjit S. Dhillon
2016	A*	`conf`	Robust Principal Component Analysis with Side Information. ICML Kai-Yang Chiang, Cho-Jui Hsieh, Inderjit S. Dhillon
2016	A*	`conf`	Square Root Graphical Models: Multivariate Generalizations of Univariate Exponential Families that Permit Positive Dependencies. ICML David I. Inouye, Pradeep Ravikumar, Inderjit S. Dhillon
2016	—	`conf`	Structured Sparse Regression via Greedy Hard Thresholding. NIPS Prateek Jain, Nikhil Rao, Inderjit S. Dhillon
2016	J	`jnl`	Structured Sparse Regression via Greedy Hard-Thresholding. CoRR Prateek Jain, Nikhil Rao, Inderjit S. Dhillon
2016	—	`conf`	Temporal Regularized Matrix Factorization for High-dimensional Time Series Prediction. NIPS Hsiang-Fu Yu, Nikhil Rao, Inderjit S. Dhillon
2015	A*	`conf`	A Convex Exemplar-based Approach to MAD-Bayes Dirichlet Process Mixture Models. ICML Ian En-Hsu Yen, Xin Lin, Kai Zhong, Pradeep Ravikumar, Inderjit S. Dhillon
2015	A*	`conf`	A Scalable Asynchronous Distributed Algorithm for Topic Modeling. WWW Hsiang-Fu Yu, Cho-Jui Hsieh, Hyokun Yun, S. V. N. Vishwanathan, Inderjit S. Dhillon
2015	A*	`conf`	Clustering to forecast sparse time-series data. ICDE Abhay Jha, Shubhankar Ray, Brian Seaman, Inderjit S. Dhillon
2015	—	`conf`	Collaborative Filtering with Graph Information: Consistency and Scalable Methods. NIPS Nikhil Rao, Hsiang-Fu Yu, Pradeep Ravikumar, Inderjit S. Dhillon
2015	—	`conf`	Consistent Multilabel Classification. NIPS Oluwasanmi Koyejo, Nagarajan Natarajan, Pradeep Ravikumar, Inderjit S. Dhillon
2015	J	`jnl`	Coordinate Descent Methods for Symmetric Nonnegative Matrix Factorization. CoRR Arnaud Vandaele, Nicolas Gillis, Qi Lei, Kai Zhong, Inderjit S. Dhillon
2015	B	`conf`	Efficient Matrix Sensing Using Rank-1 Gaussian Measurements. ALT Kai Zhong, Prateek Jain, Inderjit S. Dhillon
2015	—	`conf`	Fixed-Length Poisson MRF: Adding Dependencies to the Multinomial. NIPS David I. Inouye, Pradeep Ravikumar, Inderjit S. Dhillon
2015	—	`conf`	Matrix Completion with Noisy Side Information. NIPS Kai-Yang Chiang, Cho-Jui Hsieh, Inderjit S. Dhillon
2015	A	`conf`	Non-exhaustive, Overlapping SDM Joyce Jiyoung Whang, Inderjit S. Dhillon, David F. Gleich
2015	A*	`conf`	Non-exhaustive, Overlapping Clustering via Low-Rank Semidefinite Programming. KDD Yangyang Hou, Joyce Jiyoung Whang, David F. Gleich, Inderjit S. Dhillon
2015	J	`jnl`	Optimal Decision-Theoretic Classification Using Non-Decomposable Performance Metrics. CoRR Nagarajan Natarajan, Oluwasanmi Koyejo, Pradeep Ravikumar, Inderjit S. Dhillon
2015	J	`jnl`	Overlapping Community Detection Using Neighborhood-Inflated Seed Expansion. CoRR Joyce Jiyoung Whang, David F. Gleich, Inderjit S. Dhillon
2015	A*	`conf`	PASSCoDe: Parallel ASynchronous Stochastic dual Co-ordinate Descent. ICML Cho-Jui Hsieh, Hsiang-Fu Yu, Inderjit S. Dhillon
2015	J	`jnl`	PASSCoDe: Parallel ASynchronous Stochastic dual Co-ordinate Descent. CoRR Cho-Jui Hsieh, Hsiang-Fu Yu, Inderjit S. Dhillon
2015	A*	`conf`	PU Learning for Matrix Completion. ICML Cho-Jui Hsieh, Nagarajan Natarajan, Inderjit S. Dhillon
2015	—	`conf`	PU matrix completion with graph information. CAMSAP Nagarajan Natarajan, Nikhil Rao, Inderjit S. Dhillon
2015	A*	`conf`	Preference Completion: Large-scale Collaborative Ranking from Pairwise Comparisons. ICML Dohyung Park, Joe Neeman, Jin Zhang, Sujay Sanghavi, Inderjit S. Dhillon
2015	J	`jnl`	Preference Completion: Large-scale Collaborative Ranking from Pairwise Comparisons. CoRR Dohyung Park, Joe Neeman, Jin Zhang, Sujay Sanghavi, Inderjit S. Dhillon
2015	—	`conf`	Scalable Data-Driven PageRank: Algorithms, System Issues, and Lessons Learned. Euro-Par Joyce Jiyoung Whang, Andrew Lenharth, Inderjit S. Dhillon, Keshav Pingali
2015	—	`conf`	Sparse Linear Programming via Primal and Dual Augmented Coordinate Descent. NIPS Ian En-Hsu Yen, Kai Zhong, Cho-Jui Hsieh, Pradeep Ravikumar, Inderjit S. Dhillon
2015	J	`jnl`	Temporal Regularized Matrix Factorization. CoRR Hsiang-Fu Yu, Nikhil Rao, Inderjit S. Dhillon
2015	A	`conf`	Tumblr Blog Recommendation with Boosted Inductive Matrix Completion. CIKM Donghyuk Shin, Suleyman Cetintas, Kuang-Chih Lee, Inderjit S. Dhillon
2014	A*	`conf`	A Divide-and-Conquer Solver for Kernel Support Vector Machines. ICML Cho-Jui Hsieh, Si Si, Inderjit S. Dhillon
2014	J	`jnl`	A Scalable Asynchronous Distributed Algorithm for Topic Modeling. CoRR Hsiang-Fu Yu, Cho-Jui Hsieh, Hyokun Yun, S. V. N. Vishwanathan, Inderjit S. Dhillon
2014	A*	`conf`	Admixture of Poisson MRFs: A Topic Model with Word Dependencies. ICML David I. Inouye, Pradeep Ravikumar, Inderjit S. Dhillon
2014	—	`conf`	Capturing Semantically Meaningful Word Dependencies with an Admixture of Poisson MRFs. NIPS David I. Inouye, Pradeep Ravikumar, Inderjit S. Dhillon
2014	—	`conf`	Consistent Binary Classification with Generalized Performance Metrics. NIPS Oluwasanmi Koyejo, Nagarajan Natarajan, Pradeep Ravikumar, Inderjit S. Dhillon
2014	—	`conf`	Constant Nullspace Strong Convexity and Fast Convergence of Proximal Methods under High-Dimensional Settings. NIPS Ian En-Hsu Yen, Cho-Jui Hsieh, Pradeep Ravikumar, Inderjit S. Dhillon
2014	—	`conf`	Fast Prediction for Large-Scale Kernel Machines. NIPS Cho-Jui Hsieh, Si Si, Inderjit S. Dhillon
2014	J	`jnl`	Inductive matrix completion for predicting gene-disease associations. Bioinform. Nagarajan Natarajan, Inderjit S. Dhillon
2014	A*	`conf`	Large-scale Multi-label Learning with Missing Labels. ICML Hsiang-Fu Yu, Prateek Jain, Purushottam Kar, Inderjit S. Dhillon
2014	A*	`conf`	Memory Efficient Kernel Approximation. ICML Si Si, Cho-Jui Hsieh, Inderjit S. Dhillon
2014	—	`conf`	Multi-Scale Spectral Decomposition of Massive Graphs. NIPS Si Si, Donghyuk Shin, Inderjit S. Dhillon, Beresford N. Parlett
2014	J	`jnl`	NOMAD: Nonlocking, stOchastic Multi-machine algorithm for Asynchronous and Decentralized matrix completion. Proc. VLDB Endow. Hyokun Yun, Hsiang-Fu Yu, Cho-Jui Hsieh, S. V. N. Vishwanathan, Inderjit S. Dhillon
2014	J	`jnl`	PU Learning for Matrix Completion. CoRR Cho-Jui Hsieh, Nagarajan Natarajan, Inderjit S. Dhillon
2014	J	`jnl`	Parallel matrix factorization for recommender systems. Knowl. Inf. Syst. Hsiang-Fu Yu, Cho-Jui Hsieh, Si Si, Inderjit S. Dhillon
2014	J	`jnl`	Prediction and clustering in signed networks: a local to global perspective. J. Mach. Learn. Res. Kai-Yang Chiang, Cho-Jui Hsieh, Nagarajan Natarajan, Inderjit S. Dhillon, Ambuj Tewari
2014	—	`conf`	Proximal Quasi-Newton for Computationally Intensive L1-regularized M-estimators. NIPS Kai Zhong, Ian En-Hsu Yen, Inderjit S. Dhillon, Pradeep Ravikumar
2014	—	`conf`	QUIC & DIRTY: A Quadratic Approximation Approach for Dirty Statistical Models. NIPS Cho-Jui Hsieh, Inderjit S. Dhillon, Pradeep Ravikumar, Stephen Becker, Peder A. Olsen
2014	J	`jnl`	QUIC: quadratic approximation for sparse inverse covariance estimation. J. Mach. Learn. Res. Cho-Jui Hsieh, Mátyás A. Sustik, Inderjit S. Dhillon, Pradeep Ravikumar
2014	—	`conf`	Sparse Random Feature Algorithm as Coordinate Descent in Hilbert Space. NIPS Ian En-Hsu Yen, Ting-Wei Lin, Shou-De Lin, Pradeep Ravikumar, Inderjit S. Dhillon
2013	J	`jnl`	A Divide-and-Conquer Solver for Kernel Support Vector Machines. CoRR Cho-Jui Hsieh, Si Si, Inderjit S. Dhillon
2013	J	`jnl`	A non-monotonic method for large-scale non-negative least squares. Optim. Methods Softw. Dongmin Kim, Suvrit Sra, Inderjit S. Dhillon
2013	—	`conf`	BIG & QUIC: Sparse Inverse Covariance Estimation for a Million Variables. NIPS Cho-Jui Hsieh, Mátyás A. Sustik, Inderjit S. Dhillon, Pradeep Ravikumar, Russell A. Poldrack
2013	—	`conf`	Large Scale Distributed Sparse Precision Estimation. NIPS Huahua Wang, Arindam Banerjee, Cho-Jui Hsieh, Pradeep Ravikumar, Inderjit S. Dhillon
2013	J	`jnl`	Large-scale Multi-label Learning with Missing Labels. CoRR Hsiang-Fu Yu, Prateek Jain, Inderjit S. Dhillon
2013	—	`conf`	Learning with Noisy Labels. NIPS Nagarajan Natarajan, Inderjit S. Dhillon, Pradeep Ravikumar, Ambuj Tewari
2013	J	`jnl`	NOMAD: Non-locking, stOchastic Multi-machine algorithm for Asynchronous and Decentralized matrix completion. CoRR Hyokun Yun, Hsiang-Fu Yu, Cho-Jui Hsieh, S. V. N. Vishwanathan, Inderjit S. Dhillon
2013	A	`conf`	Overlapping community detection using seed set expansion. CIKM Joyce Jiyoung Whang, David F. Gleich, Inderjit S. Dhillon
2013	J	`jnl`	Prediction and Clustering in Signed Networks: A Local to Global Perspective CoRR Kai-Yang Chiang, Cho-Jui Hsieh, Nagarajan Natarajan, Ambuj Tewari, Inderjit S. Dhillon
2013	J	`jnl`	Provable Inductive Matrix Completion. CoRR Prateek Jain, Inderjit S. Dhillon
2013	Misc	`conf`	Scalable Network Analysis. COMAD Inderjit S. Dhillon
2013	J	`jnl`	Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation. CoRR Cho-Jui Hsieh, Mátyás A. Sustik, Inderjit S. Dhillon, Pradeep Ravikumar
2013	A*	`conf`	Stochastic Blockmodel with Cluster Overlap, Relevance Selection, and Similarity-Based Smoothing. ICDM Joyce Jiyoung Whang, Piyush Rai, Inderjit S. Dhillon
2013	A*	`ed.`	The 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2013, Chicago, IL, USA, August 11-14, 2013 KDD Inderjit S. Dhillon, Yehuda Koren, Rayid Ghani, Ted E. Senator, Paul Bradley, Rajesh Parekh, Jingrui He, Robert L. Grossman, Ramasamy Uthurusamy
2013	A	`conf`	Which app will you use next?: collaborative filtering with interactional context. RecSys Nagarajan Natarajan, Donghyuk Shin, Inderjit S. Dhillon
2012	—	`conf`	A Divide-and-Conquer Method for Sparse Inverse Covariance Estimation. NIPS Cho-Jui Hsieh, Inderjit S. Dhillon, Pradeep Ravikumar, Arindam Banerjee
2012	A*	`conf`	Clustered embedding of massive social networks. SIGMETRICS Han Hee Song, Berkant Savas, Tae Won Cho, Vacha Dave, Zhengdong Lu, Inderjit S. Dhillon, Yin Zhang, Lili Qiu
2012	A*	`conf`	Low rank modeling of signed networks. KDD Cho-Jui Hsieh, Kai-Yang Chiang, Inderjit S. Dhillon
2012	J	`jnl`	Metric and Kernel Learning Using a Linear Transformation. J. Mach. Learn. Res. Prateek Jain, Brian Kulis, Jason V. Davis, Inderjit S. Dhillon
2012	J	`jnl`	Multi-Scale Link Prediction CoRR Donghyuk Shin, Si Si, Inderjit S. Dhillon
2012	A	`conf`	Multi-scale link prediction. CIKM Donghyuk Shin, Si Si, Inderjit S. Dhillon
2012	J	`jnl`	On a Zero-Finding Problem Involving the Matrix Exponential. SIAM J. Matrix Anal. Appl. Mátyás A. Sustik, Inderjit S. Dhillon
2012	—	`conf`	Parallel Clustered Low-Rank Approximation of Graphs and Its Application to Link Prediction. LCPC Xin Sui, Tsung-Hsien Lee, Joyce Jiyoung Whang, Berkant Savas, Saral Jain, Keshav Pingali, Inderjit S. Dhillon
2012	A*	`conf`	Scalable Coordinate Descent Approaches to Parallel Matrix Factorization for Recommender Systems. ICDM Hsiang-Fu Yu, Cho-Jui Hsieh, Si Si, Inderjit S. Dhillon
2012	A*	`conf`	Scalable and Memory-Efficient Clustering of Large-Scale Social Networks. ICDM Joyce Jiyoung Whang, Xin Sui, Inderjit S. Dhillon
2012	A	`conf`	Scalable clustering of signed networks using balance normalized cut. CIKM Kai-Yang Chiang, Joyce Jiyoung Whang, Inderjit S. Dhillon
2012	—	`conf`	Sparse inverse covariance matrix estimation using quadratic approximation. MLSLP Inderjit S. Dhillon, Cho-Jui Hsieh, Mátyás A. Sustik, Pradeep Ravikumar
2011	A	`conf`	Clustered low rank approximation of graphs in information science applications. SDM Berkant Savas, Inderjit S. Dhillon
2011	A	`conf`	Exploiting longer cycles for link prediction in signed networks. CIKM Kai-Yang Chiang, Nagarajan Natarajan, Ambuj Tewari, Inderjit S. Dhillon
2011	A*	`conf`	Fast coordinate descent methods with variable selection for non-negative matrix factorization. KDD Cho-Jui Hsieh, Inderjit S. Dhillon
2011	—	`conf`	Greedy Algorithms for Structurally Constrained High Dimensional Problems. NIPS Ambuj Tewari, Pradeep Ravikumar, Inderjit S. Dhillon
2011	—	`conf`	Nearest Neighbor based Greedy Coordinate Descent. NIPS Inderjit S. Dhillon, Pradeep Ravikumar, Ambuj Tewari
2011	J	`jnl`	Orthogonal Matching Pursuit with Replacement CoRR Prateek Jain, Ambuj Tewari, Inderjit S. Dhillon
2011	—	`conf`	Orthogonal Matching Pursuit with Replacement. NIPS Prateek Jain, Ambuj Tewari, Inderjit S. Dhillon
2011	J	`jnl`	Preface. Math. Program. Alexandre d'Aspremont, Francis R. Bach, Inderjit S. Dhillon, Bin Yu
2011	J	`jnl`	Scalable Affiliation Recommendation using Auxiliary Networks. ACM Trans. Intell. Syst. Technol. Vishvas Vasuki, Nagarajan Natarajan, Zhengdong Lu, Berkant Savas, Inderjit S. Dhillon
2011	—	`conf`	Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation. NIPS Cho-Jui Hsieh, Mátyás A. Sustik, Inderjit S. Dhillon, Pradeep Ravikumar
2010	A*	`conf`	A scalable trust-region algorithm with application to mixed-norm regression. ICML Dongmin Kim, Suvrit Sra, Inderjit S. Dhillon
2010	A	`conf`	Affiliation recommendation using auxiliary networks. RecSys Vishvas Vasuki, Nagarajan Natarajan, Zhengdong Lu, Inderjit S. Dhillon
2010	—	`conf`	Guaranteed Rank Minimization via Singular Value Projection. NIPS Prateek Jain, Raghu Meka, Inderjit S. Dhillon
2010	—	`conf`	Inductive Regularized Learning of Kernel Functions. NIPS Prateek Jain, Brian Kulis, Inderjit S. Dhillon
2010	A*	`conf`	Supervised Link Prediction Using Multiple Sources. ICDM Zhengdong Lu, Berkant Savas, Wei Tang, Inderjit S. Dhillon
2010	J	`jnl`	Tackling Box-Constrained Optimization via a New Projected Quasi-Newton Approach. SIAM J. Sci. Comput. Dongmin Kim, Suvrit Sra, Inderjit S. Dhillon
2009	A*	`conf`	A scalable framework for discovering coherent co-clusters in noisy data. ICML Meghana Deodhar, Gunjan Gupta, Joydeep Ghosh, Hyuk Cho, Inderjit S. Dhillon
2009	A	`conf`	A spatio-temporal approach to collaborative filtering. RecSys Zhengdong Lu, Deepak Agarwal, Inderjit S. Dhillon
2009	A*	`conf`	Clustering with Multiple Graphs. ICDM Wei Tang, Zhengdong Lu, Inderjit S. Dhillon
2009	A	`conf`	Convex Perturbations for Scalable Semidefinite Programming. AISTATS Brian Kulis, Suvrit Sra, Inderjit S. Dhillon
2009	A*	`conf`	Geometry-aware metric learning. ICML Zhengdong Lu, Prateek Jain, Inderjit S. Dhillon
2009	J	`jnl`	Guaranteed Rank Minimization via Singular Value Projection CoRR Raghu Meka, Prateek Jain, Inderjit S. Dhillon
2009	—	`ch.`	Knowledge Discovery: Clustering. Encyclopedia of Complexity and Systems Science Pavel Berkhin, Inderjit S. Dhillon
2009	J	`jnl`	Low-Rank Kernel Learning with Bregman Matrix Divergences. J. Mach. Learn. Res. Brian Kulis, Mátyás A. Sustik, Inderjit S. Dhillon
2009	—	`conf`	Matrix Completion from Power-Law Distributed Samples. NIPS Raghu Meka, Prateek Jain, Inderjit S. Dhillon
2009	J	`jnl`	Metric and Kernel Learning using a Linear Transformation. CoRR Prateek Jain, Brian Kulis, Jason V. Davis, Inderjit S. Dhillon
2009	J	`jnl`	Semi-supervised graph clustering: a kernel approach. Mach. Learn. Brian Kulis, Sugato Basu, Inderjit S. Dhillon, Raymond J. Mooney
2008	J	`jnl`	Coclustering of Human Cancer Microarrays Using Minimum Sum-Squared Residue Coclustering. IEEE ACM Trans. Comput. Biol. Bioinform. Hyuk Cho, Inderjit S. Dhillon
2008	J	`jnl`	Constructing Packings in Grassmannian Manifolds via Alternating Projection. Exp. Math. Inderjit S. Dhillon, Robert W. Heath Jr., Thomas Strohmer, Joel A. Tropp
2008	J	`jnl`	Fast Projection-Based Methods for the Least Squares Nonnegative Matrix Approximation Problem. Stat. Anal. Data Min. Dongmin Kim, Suvrit Sra, Inderjit S. Dhillon
2008	—	`conf`	Hunting for Coherent Co-clusters in High Dimensional and Noisy Datasets. ICDM Workshops Meghana Deodhar, Joydeep Ghosh, Gunjan Gupta, Hyuk Cho, Inderjit S. Dhillon
2008	—	`conf`	Online Metric Learning and Fast Similarity Search. NIPS Prateek Jain, Brian Kulis, Inderjit S. Dhillon, Kristen Grauman
2008	A*	`conf`	Rank minimization via online learning. ICML Raghu Meka, Prateek Jain, Constantine Caramanis, Inderjit S. Dhillon
2008	A	`conf`	Simultaneous Unsupervised Learning of Disparate Clusterings. SDM Prateek Jain, Raghu Meka, Inderjit S. Dhillon
2008	J	`jnl`	Simultaneous Unsupervised Learning of Disparate Clusterings. Stat. Anal. Data Min. Prateek Jain, Raghu Meka, Inderjit S. Dhillon
2008	A*	`conf`	Structured metric learning for high dimensional problems. KDD Jason V. Davis, Inderjit S. Dhillon
2008	J	`jnl`	The Metric Nearness Problem. SIAM J. Matrix Anal. Appl. Justin Brickell, Inderjit S. Dhillon, Suvrit Sra, Joel A. Tropp
2007	J	`jnl`	A Generalized Maximum Entropy Approach to Bregman Co-clustering and Matrix Approximation. J. Mach. Learn. Res. Arindam Banerjee, Inderjit S. Dhillon, Joydeep Ghosh, Srujana Merugu, Dharmendra S. Modha
2007	A	`conf`	Fast Newton-type Methods for the Least Squares Nonnegative Matrix Approximation Problem. SDM Dongmin Kim, Suvrit Sra, Inderjit S. Dhillon
2007	A*	`conf`	Information-theoretic metric learning. ICML Jason V. Davis, Brian Kulis, Prateek Jain, Suvrit Sra, Inderjit S. Dhillon
2007	J	`jnl`	Matrix Nearness Problems with Bregman Divergences. SIAM J. Matrix Anal. Appl. Inderjit S. Dhillon, Joel A. Tropp
2007	J	`jnl`	Weighted Graph Cuts without Eigenvectors A Multilevel Approach. IEEE Trans. Pattern Anal. Mach. Intell. Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis
2006	—	`conf`	Adaptive Website Design Using Caching Algorithms. WebKDD Justin Brickell, Inderjit S. Dhillon, Dharmendra S. Modha
2006	—	`ch.`	Clustering with Entropy-Like Grouping Multidimensional Data Marc Teboulle, Pavel Berkhin, Inderjit S. Dhillon, Yuqiang Guan, Jacob Kogan
2006	—	`conf`	Differential Entropic Clustering of Multivariate Gaussians. NIPS Jason V. Davis, Inderjit S. Dhillon
2006	A*	`conf`	Estimating the global pagerank of web communities. KDD Jason V. Davis, Inderjit S. Dhillon
2006	A*	`conf`	Learning low-rank kernel matrices. ICML Brian Kulis, Mátyás A. Sustik, Inderjit S. Dhillon
2006	J	`jnl`	The design and implementation of the MRRR algorithm. ACM Trans. Math. Softw. Inderjit S. Dhillon, Beresford N. Parlett, Christof Vömel
2005	J	`jnl`	A Parallel Eigensolver for Dense Symmetric Matrices Based on Multiple Relatively Robust Representations. SIAM J. Sci. Comput. Paolo Bientinesi, Inderjit S. Dhillon, Robert A. van de Geijn
2005	A*	`conf`	A fast kernel-based multilevel algorithm for graph clustering. KDD Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis
2005	J	`jnl`	Clustering on the Unit Hypersphere using von Mises-Fisher Distributions. J. Mach. Learn. Res. Arindam Banerjee, Inderjit S. Dhillon, Joydeep Ghosh, Suvrit Sra
2005	J	`jnl`	Clustering with Bregman Divergences. J. Mach. Learn. Res. Arindam Banerjee, Srujana Merugu, Inderjit S. Dhillon, Joydeep Ghosh
2005	J	`jnl`	Designing structured tight frames via an alternating projection method. IEEE Trans. Inf. Theory Joel A. Tropp, Inderjit S. Dhillon, Robert W. Heath Jr., Thomas Strohmer
2005	J	`jnl`	Generalized Finite Algorithms for Constructing Hermitian Matrices with Prescribed Diagonal and Spectrum. SIAM J. Matrix Anal. Appl. Inderjit S. Dhillon, Robert W. Heath Jr., Mátyás A. Sustik, Joel A. Tropp
2005	—	`conf`	Generalized Nonnegative Matrix Approximations with Bregman Divergences. NIPS Inderjit S. Dhillon, Suvrit Sra
2005	J	`jnl`	Glued Matrices and the MRRR Algorithm. SIAM J. Sci. Comput. Inderjit S. Dhillon, Beresford N. Parlett, Christof Vömel
2005	A*	`conf`	Semi-supervised graph clustering: a kernel approach. ICML Brian Kulis, Sugato Basu, Inderjit S. Dhillon, Raymond J. Mooney
2004	A*	`conf`	A generalized maximum entropy approach to bregman co-clustering and matrix approximation. KDD Arindam Banerjee, Inderjit S. Dhillon, Joydeep Ghosh, Srujana Merugu, Dharmendra S. Modha
2004	A*	`conf`	An information theoretic analysis of maximum likelihood mixture estimation for exponential families. ICML Arindam Banerjee, Inderjit S. Dhillon, Joydeep Ghosh, Srujana Merugu
2004	A	`conf`	Clustering with Bregman Divergences. SDM Arindam Banerjee, Srujana Merugu, Inderjit S. Dhillon, Joydeep Ghosh
2004	J	`jnl`	Finite-Step Algorithms for Constructing Optimal CDMA Signature Sequences. IEEE Trans. Inf. Theory Joel A. Tropp, Inderjit S. Dhillon, Robert W. Heath Jr.
2004	A*	`conf`	Kernel k-means: spectral clustering and normalized cuts. KDD Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis
2004	A	`conf`	Minimum Sum-Squared Residue Co-Clustering of Gene Expression Data. SDM Hyuk Cho, Inderjit S. Dhillon, Yuqiang Guan, Suvrit Sra
2004	—	`conf`	Triangle Fixing Algorithms for the Metric Nearness Problem. NIPS Inderjit S. Dhillon, Suvrit Sra, Joel A. Tropp
2003	J	`jnl`	A Divisive Information-Theoretic Feature Clustering Algorithm for Text Classification. J. Mach. Learn. Res. Inderjit S. Dhillon, Subramanyam Mallela, Rahul Kumar
2003	J	`jnl`	Diametrical clustering for identifying anti-correlated gene clusters. Bioinform. Inderjit S. Dhillon, Edward M. Marcotte, Usman Roshan
2003	A*	`conf`	Generative model-based clustering of directional data. KDD Arindam Banerjee, Inderjit S. Dhillon, Joydeep Ghosh, Suvrit Sra
2003	A*	`conf`	Information Theoretic Clustering of Sparse Co-Occurrence Data. ICDM Inderjit S. Dhillon, Yuqiang Guan
2003	A*	`conf`	Information-theoretic co-clustering. KDD Inderjit S. Dhillon, Subramanyam Mallela, Dharmendra S. Modha
2003	J	`jnl`	Orthogonal Eigenvectors and Relative Gaps. SIAM J. Matrix Anal. Appl. Inderjit S. Dhillon, Beresford N. Parlett
2002	J	`jnl`	Class visualization of high-dimensional data with applications. Comput. Stat. Data Anal. Inderjit S. Dhillon, Dharmendra S. Modha, W. Scott Spangler
2002	A*	`conf`	Enhanced word clustering for hierarchical text classification. KDD Inderjit S. Dhillon, Subramanyam Mallela, Rahul Kumar
2002	A*	`conf`	Iterative Clustering of High Dimensional Text Data Augmented by Local Search. ICDM Inderjit S. Dhillon, Yuqiang Guan, Jacob Kogan
2001	A*	`conf`	Co-clustering documents and words using bipartite spectral graph partitioning. KDD Inderjit S. Dhillon
2001	J	`jnl`	Concept Decompositions for Large Sparse Text Data Using Clustering. Mach. Learn. Inderjit S. Dhillon, Dharmendra S. Modha
1999	—	`conf`	A Data-Clustering Algorithm on Distributed Memory Multiprocessors. Large-Scale Parallel Data Mining Inderjit S. Dhillon, Dharmendra S. Modha
1998	J	`jnl`	Reliable Computation of the Condition Number of a Tridiagonal Matrix in SIAM J. Matrix Anal. Appl. Inderjit S. Dhillon
1997	—	`conf`	Application of a New Algorithm for the Symmetric Eigenproblem to Computational Quantum Chemistry. PP Inderjit S. Dhillon, George Fann, Beresford N. Parlett
1997	J	`jnl`	Practical Experience in the Numerical Dangers of Heterogeneous Computing. ACM Trans. Math. Softw. 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
1997	—	`conf`	ScaLAPACK: A Linear Algebra Library for Message-Passing Computers. PP 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, R. Clinton Whaley
1996	—	`conf`	Practical Experience in the Dangers of Heterogeneous Computing. PARA Andrew J. Cleary, James Demmel, Inderjit S. Dhillon, Jack J. Dongarra, Sven Hammarling, Antoine Petitet, H. Ren, Ken Stanley, R. Clinton Whaley
1996	A	`conf`	ScaLAPACK: A Portable Linear Algebra Library for Distributed Memory Computers - Design Issues and Performance. SC 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
1995	—	`conf`	ScaLAPACK: A Portable Linear Algebra Library for Distributed Memory Computers - Design Issues and Performance. PARA Jaeyoung Choi, James Demmel, Inderjit S. Dhillon, Jack J. Dongarra, Susan Ostrouchov, Antoine Petitet, Ken Stanley, David W. Walker, R. Clinton Whaley