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ORCIDInderjit S. Dhillon
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- affiliation: University of Texas at Austin, USA
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2020 – today
- 2024
[j49]Haoya Li
, Hsiang-Fu Yu, Lexing Ying, Inderjit S. Dhillon:
Accelerating Primal-Dual Methods for Regularized Markov Decision Processes. SIAM J. Optim. 34(1): 764-789 (2024)- [c168]Cho-Jui Hsieh, Si Si, Felix Yu, Inderjit S. Dhillon:
Automatic Engineering of Long Prompts. ACL (Findings) 2024: 10672-10685 - [c167]Arjun R. Akula, Garima Pruthi, Inderjit S. Dhillon, Pradyumna Narayana, Sugato Basu, Varun Jampani:
PRISM: A New Lens for Improved Color Understanding. EMNLP (Industry Track) 2024: 1659-1670 - [c166]Sai Surya Duvvuri, Devvrit, Rohan Anil, Cho-Jui Hsieh, Inderjit S. Dhillon:
Combining Axes Preconditioners through Kronecker Approximation for Deep Learning. ICLR 2024 - [c165]Nilesh Gupta, Devvrit, Ankit Singh Rawat, Srinadh Bhojanapalli, Prateek Jain, Inderjit S. Dhillon:
Dual-Encoders for Extreme Multi-label Classification. ICLR 2024 - [c164]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 - [i81]Rudrajit Das, Naman Agarwal, Sujay Sanghavi, Inderjit S. Dhillon:
Towards Quantifying the Preconditioning Effect of Adam. CoRR abs/2402.07114 (2024) - [i80]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 abs/2406.11206 (2024) - [i79]Anish Acharya, Inderjit S. Dhillon, Sujay Sanghavi:
Geometric Median (GM) Matching for Robust Data Pruning. CoRR abs/2406.17188 (2024) - [i78]Ruochen Wang, Si Si, Felix Yu, Dorothea Wiesmann, Cho-Jui Hsieh, Inderjit S. Dhillon:
Large Language Models are Interpretable Learners. CoRR abs/2406.17224 (2024) - [i77]Jui-Nan Yen, Si Si, Zhao Meng, Felix X. Yu, Sai Surya Duvvuri, Inderjit S. Dhillon, Cho-Jui Hsieh, Sanjiv Kumar:
LoRA Done RITE: Robust Invariant Transformation Equilibration for LoRA Optimization. CoRR abs/2410.20625 (2024) - 2023
- [j48]Haoya Li, Samarth Gupta, Hsiang-Fu Yu, Lexing Ying, Inderjit S. Dhillon:
Approximate Newton Policy Gradient Algorithms. SIAM J. Sci. Comput. 45(5): 2585- (2023) - [c163]Shuo Yang, Yijun Dong, Rachel A. Ward, Inderjit S. Dhillon, Sujay Sanghavi, Qi Lei:
Sample Efficiency of Data Augmentation Consistency Regularization. AISTATS 2023: 3825-3853 - [c162]Devvrit, Sai Surya Duvvuri, Rohan Anil, Vineet Gupta, Cho-Jui Hsieh, Inderjit S. Dhillon:
A Computationally Efficient Sparsified Online Newton Method. NeurIPS 2023 - [c161]Jui-Nan Yen, Sai Surya Duvvuri, Inderjit S. Dhillon, Cho-Jui Hsieh:
Block Low-Rank Preconditioner with Shared Basis for Stochastic Optimization. NeurIPS 2023 - [c160]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: 3225-3235 - [i76]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 abs/2310.07707 (2023) - [i75]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 abs/2310.08891 (2023) - [i74]Nilesh Gupta, Devvrit Khatri, Ankit Singh Rawat, Srinadh Bhojanapalli, Prateek Jain, Inderjit S. Dhillon:
Efficacy of Dual-Encoders for Extreme Multi-Label Classification. CoRR abs/2310.10636 (2023) - [i73]Devvrit, Sai Surya Duvvuri, Rohan Anil, Vineet Gupta, Cho-Jui Hsieh, Inderjit S. Dhillon:
A Computationally Efficient Sparsified Online Newton Method. CoRR abs/2311.10085 (2023) - [i72]Cho-Jui Hsieh, Si Si, Felix X. Yu, Inderjit S. Dhillon:
Automatic Engineering of Long Prompts. CoRR abs/2311.10117 (2023) - 2022
- [j47]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: 98:1-98:32 (2022) - [j46]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): 2727-2739 (2022) - [c159]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: 11145-11168 - [c158]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 - [c157]Shuo Yang, Tongzheng Ren, Sanjay Shakkottai, Eric Price, Inderjit S. Dhillon, Sujay Sanghavi:
Linear Bandit Algorithms with Sublinear Time Complexity. ICML 2022: 25241-25260 - [c156]Minhao Cheng, Qi Lei, Pin-Yu Chen, Inderjit S. Dhillon, Cho-Jui Hsieh:
CAT: Customized Adversarial Training for Improved Robustness. IJCAI 2022: 673-679 - [c155]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: 5455-5468 - [c154]Devvrit, Aditya Sinha, Inderjit S. Dhillon, Prateek Jain:
S3GC: Scalable Self-Supervised Graph Clustering. NeurIPS 2022 - [c153]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 - [c152]Adam Block, Rahul Kidambi, Daniel N. Hill, Thorsten Joachims, Inderjit S. Dhillon:
Counterfactual Learning To Rank for Utility-Maximizing Query Autocompletion. SIGIR 2022: 791-802 - [c151]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: 496-506 - [c150]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: 452-461 - [i71]Haoya Li, Hsiang-Fu Yu, Lexing Ying, Inderjit S. Dhillon:
Accelerating Primal-dual Methods for Regularized Markov Decision Processes. CoRR abs/2202.10506 (2022) - [i70]Shuo Yang, Yijun Dong, Rachel A. Ward, Inderjit S. Dhillon, Sujay Sanghavi, Qi Lei:
Sample Efficiency of Data Augmentation Consistency Regularization. CoRR abs/2202.12230 (2022) - [i69]Adam Block, Rahul Kidambi, Daniel N. Hill, Thorsten Joachims, Inderjit S. Dhillon:
Counterfactual Learning To Rank for Utility-Maximizing Query Autocompletion. CoRR abs/2204.10936 (2022) - [i68]Anish Acharya, Sujay Sanghavi, Li Jing, Bhargav Bhushanam, Dhruv Choudhary, Michael G. Rabbat, Inderjit S. Dhillon:
Positive Unlabeled Contrastive Learning. CoRR abs/2206.01206 (2022) - [i67]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 abs/2206.11408 (2022) - [i66]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 abs/2210.08410 (2022) - [i65]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 abs/2211.00635 (2022) - 2021
- [c149]Romain Lopez, Inderjit S. Dhillon, Michael I. Jordan:
Learning from eXtreme Bandit Feedback. AAAI 2021: 8732-8740 - [c148]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: 3717-3726 - [c147]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. ICML 2021: 9422-9433 - [c146]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:
Extreme Multi-label Learning for Semantic Matching in Product Search. KDD 2021: 2643-2651 - [c145]Nishant Yadav, Rajat Sen, Daniel N. Hill, Arya Mazumdar, Inderjit S. Dhillon:
Session-Aware Query Auto-completion using Extreme Multi-Label Ranking. KDD 2021: 3835-3844 - [c144]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: 7267-7280 - [c143]Xuanqing Liu, Wei-Cheng Chang, Hsiang-Fu Yu, Cho-Jui Hsieh, Inderjit S. Dhillon:
Label Disentanglement in Partition-based Extreme Multilabel Classification. NeurIPS 2021: 15359-15369 - [c142]Patrick H. Chen, Hsiang-Fu Yu, Inderjit S. Dhillon, Cho-Jui Hsieh:
DRONE: Data-aware Low-rank Compression for Large NLP Models. NeurIPS 2021: 29321-29334 - [i64]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 abs/2102.07800 (2021) - [i63]Shuo Yang, Tongzheng Ren, Sanjay Shakkottai, Eric Price, Inderjit S. Dhillon, Sujay Sanghavi:
Linear Bandit Algorithms with Sublinear Time Complexity. CoRR abs/2103.02729 (2021) - [i62]Shuo Yang, Tongzheng Ren, Inderjit S. Dhillon, Sujay Sanghavi:
Combinatorial Bandits without Total Order for Arms. CoRR abs/2103.02741 (2021) - [i61]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 abs/2106.00730 (2021) - [i60]Philip A. Etter, Kai Zhong, Hsiang-Fu Yu, Lexing Ying, Inderjit S. Dhillon:
Accelerating Inference for Sparse Extreme Multi-Label Ranking Trees. CoRR abs/2106.02697 (2021) - [i59]Rudrajit Das, Abolfazl Hashemi, Sujay Sanghavi, Inderjit S. Dhillon:
DP-NormFedAvg: Normalizing Client Updates for Privacy-Preserving Federated Learning. CoRR abs/2106.07094 (2021) - [i58]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 abs/2106.08882 (2021) - [i57]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:
Extreme Multi-label Learning for Semantic Matching in Product Search. CoRR abs/2106.12657 (2021) - [i56]Xuanqing Liu, Wei-Cheng Chang, Hsiang-Fu Yu, Cho-Jui Hsieh, Inderjit S. Dhillon:
Label Disentanglement in Partition-based Extreme Multilabel Classification. CoRR abs/2106.12751 (2021) - [i55]Jiong Zhang, Wei-Cheng Chang, Hsiang-Fu Yu, Inderjit S. Dhillon:
Fast Multi-Resolution Transformer Fine-tuning for Extreme Multi-label Text Classification. CoRR abs/2110.00685 (2021) - [i54]Haoya Li, Samarth Gupta, Hsiang-Fu Yu, Lexing Ying, Inderjit S. Dhillon:
Quasi-Newton policy gradient algorithms. CoRR abs/2110.02398 (2021) - [i53]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 abs/2110.14011 (2021) - [i52]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 abs/2111.00064 (2021) - [i51]Yuanhao Xiong, Wei-Cheng Chang, Cho-Jui Hsieh, Hsiang-Fu Yu, Inderjit S. Dhillon:
Extreme Zero-Shot Learning for Extreme Text Classification. CoRR abs/2112.08652 (2021) - 2020
- [c141]Xuanqing Liu, Hsiang-Fu Yu, Inderjit S. Dhillon, Cho-Jui Hsieh:
Learning to Encode Position for Transformer with Continuous Dynamical Model. ICML 2020: 6327-6335 - [c140]Yanyao Shen, Hsiang-Fu Yu, Sujay Sanghavi, Inderjit S. Dhillon:
Extreme Multi-label Classification from Aggregated Labels. ICML 2020: 8752-8762 - [c139]Wei-Cheng Chang, Hsiang-Fu Yu, Kai Zhong, Yiming Yang, Inderjit S. Dhillon:
Taming Pretrained Transformers for Extreme Multi-label Text Classification. KDD 2020: 3163-3171 - [c138]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: 593-602 - [e2]Inderjit S. Dhillon, Dimitris S. Papailiopoulos, Vivienne Sze:
Proceedings of the Third Conference on Machine Learning and Systems, MLSys 2020, Austin, TX, USA, March 2-4, 2020. mlsys.org 2020 [contents] - [i50]Minhao Cheng, Qi Lei, Pin-Yu Chen, Inderjit S. Dhillon, Cho-Jui Hsieh:
CAT: Customized Adversarial Training for Improved Robustness. CoRR abs/2002.06789 (2020) - [i49]Xuanqing Liu, Hsiang-Fu Yu, Inderjit S. Dhillon, Cho-Jui Hsieh:
Learning to Encode Position for Transformer with Continuous Dynamical Model. CoRR abs/2003.09229 (2020) - [i48]Yanyao Shen, Hsiang-Fu Yu, Sujay Sanghavi, Inderjit S. Dhillon:
Extreme Multi-label Classification from Aggregated Labels. CoRR abs/2004.00198 (2020) - [i47]Joyce Jiyoung Whang, Inderjit S. Dhillon:
Non-Exhaustive, Overlapping Co-Clustering: An Extended Analysis. CoRR abs/2004.11530 (2020) - [i46]Romain Lopez, Inderjit S. Dhillon, Michael I. Jordan:
Learning from eXtreme Bandit Feedback. CoRR abs/2009.12947 (2020) - [i45]Hsiang-Fu Yu, Kai Zhong, Inderjit S. Dhillon:
PECOS: Prediction for Enormous and Correlated Output Spaces. CoRR abs/2010.05878 (2020) - [i44]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 abs/2011.10643 (2020) - [i43]Devvrit, Minhao Cheng, Cho-Jui Hsieh, Inderjit S. Dhillon:
Voting based ensemble improves robustness of defensive models. CoRR abs/2011.14031 (2020) - [i42]Rudrajit Das, Abolfazl Hashemi, Sujay Sanghavi, Inderjit S. Dhillon:
Improved Convergence Rates for Non-Convex Federated Learning with Compression. CoRR abs/2012.04061 (2020) - [i41]Nishant Yadav, Rajat Sen, Daniel N. Hill, Arya Mazumdar, Inderjit S. Dhillon:
Session-Aware Query Auto-completion using Extreme Multi-label Ranking. CoRR abs/2012.07654 (2020)
2010 – 2019
- 2019
- [j45]Joyce Jiyoung Whang, Yangyang Hou, David F. Gleich, Inderjit S. Dhillon:
Non-Exhaustive, Overlapping Clustering. IEEE Trans. Pattern Anal. Mach. Intell. 41(11): 2644-2659 (2019) - [c137]Anish Acharya, Rahul Goel, Angeliki Metallinou, Inderjit S. Dhillon:
Online Embedding Compression for Text Classification Using Low Rank Matrix Factorization. AAAI 2019: 6196-6203 - [c136]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: 935-943 - [c135]Hsiang-Fu Yu, Cho-Jui Hsieh, Inderjit S. Dhillon:
Parallel Asynchronous Stochastic Coordinate Descent with Auxiliary Variables. AISTATS 2019: 2641-2649 - [c134]Inderjit S. Dhillon:
Abstract of the Keynotes. IC3 2019: 1-2 - [c133]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 - [c132]Qi Lei, Jinfeng Yi, Roman Vaculín, Lingfei Wu, Inderjit S. Dhillon:
Similarity Preserving Representation Learning for Time Series Clustering. IJCAI 2019: 2845-2851 - [c131]Qi Lei, Lingfei Wu, Pin-Yu Chen, Alex Dimakis, Inderjit S. Dhillon, Michael Witbrock:
Discrete Adversarial Attacks and Submodular Optimization with Applications to Text Classification. SysML 2019 - [c130]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: 4838-4847 - [c129]Jiong Zhang, Hsiang-Fu Yu, Inderjit S. Dhillon:
AutoAssist: A Framework to Accelerate Training of Deep Neural Networks. NeurIPS 2019: 5996-6006 - [c128]Kai Zhong, Zhao Song, Prateek Jain, Inderjit S. Dhillon:
Provable Non-linear Inductive Matrix Completion. NeurIPS 2019: 11435-11445 - [c127]Qi Lei, Jiacheng Zhuo, Constantine Caramanis, Inderjit S. Dhillon, Alexandros G. Dimakis:
Primal-Dual Block Generalized Frank-Wolfe. NeurIPS 2019: 13866-13875 - [c126]Qi Lei, Ajil Jalal, Inderjit S. Dhillon, Alexandros G. Dimakis:
Inverting Deep Generative models, One layer at a time. NeurIPS 2019: 13910-13919 - [i40]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 abs/1901.04684 (2019) - [i39]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 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 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:
SysML: The New Frontier of Machine Learning Systems. CoRR abs/1904.03257 (2019) - [i38]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 abs/1905.02331 (2019) - [i37]Jiong Zhang, Hsiang-Fu Yu, Inderjit S. Dhillon:
AutoAssist: A Framework to Accelerate Training of Deep Neural Networks. CoRR abs/1905.03381 (2019) - [i36]Rajat Sen, Hsiang-Fu Yu, Inderjit S. Dhillon:
Think Globally, Act Locally: A Deep Neural Network Approach to High-Dimensional Time Series Forecasting. CoRR abs/1905.03806 (2019) - [i35]Qi Lei, Jiacheng Zhuo, Constantine Caramanis, Inderjit S. Dhillon, Alexandros G. Dimakis:
Primal-Dual Block Frank-Wolfe. CoRR abs/1906.02436 (2019) - [i34]Qi Lei, Ajil Jalal, Inderjit S. Dhillon, Alexandros G. Dimakis:
Inverting Deep Generative models, One layer at a time. CoRR abs/1906.07437 (2019) - [i33]Vikas K. Garg, Inderjit S. Dhillon, Hsiang-Fu Yu:
Multiresolution Transformer Networks: Recurrence is Not Essential for Modeling Hierarchical Structure. CoRR abs/1908.10408 (2019) - 2018
- [j44]Kai-Yang Chiang, Inderjit S. Dhillon, Cho-Jui Hsieh:
Using Side Information to Reliably Learn Low-Rank Matrices from Missing and Corrupted Observations. J. Mach. Learn. Res. 19: 76:1-76:35 (2018) - [c125]Tsui-Wei Weng, Huan Zhang, Hongge Chen, Zhao Song, Cho-Jui Hsieh, Luca Daniel, Duane S. Boning, Inderjit S. Dhillon:
Towards Fast Computation of Certified Robustness for ReLU Networks. ICML 2018: 5273-5282 - [c124]Jiong Zhang, Qi Lei, Inderjit S. Dhillon:
Stabilizing Gradients for Deep Neural Networks via Efficient SVD Parameterization. ICML 2018: 5801-5809 - [c123]Jiong Zhang, Yibo Lin, Zhao Song, Inderjit S. Dhillon:
Learning Long Term Dependencies via Fourier Recurrent Units. ICML 2018: 5810-5818 - [c122]Po-Wei Wang, Huan Zhang, Vijai Mohan, Inderjit S. Dhillon, J. Zico Kolter:
Realtime Query Completion via Deep Language Models. eCOM@SIGIR 2018 - [i32]Jiong Zhang, Yibo Lin, Zhao Song, Inderjit S. Dhillon:
Learning Long Term Dependencies via Fourier Recurrent Units. CoRR abs/1803.06585 (2018) - [i31]Jiong Zhang, Qi Lei, Inderjit S. Dhillon:
Stabilizing Gradients for Deep Neural Networks via Efficient SVD Parameterization. CoRR abs/1803.09327 (2018) - [i30]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 abs/1804.09699 (2018) - [i29]Kai Zhong, Zhao Song, Prateek Jain, Inderjit S. Dhillon:
Nonlinear Inductive Matrix Completion based on One-layer Neural Networks. CoRR abs/1805.10477 (2018) - [i28]Anish Acharya, Rahul Goel, Angeliki Metallinou, Inderjit S. Dhillon:
Online Embedding Compression for Text Classification using Low Rank Matrix Factorization. CoRR abs/1811.00641 (2018) - [i27]Qi Lei, Lingfei Wu, Pin-Yu Chen, Alexandros G. Dimakis, Inderjit S. Dhillon, Michael Witbrock:
Discrete Attacks and Submodular Optimization with Applications to Text Classification. CoRR abs/1812.00151 (2018) - 2017
- [j43]Si Si, Cho-Jui Hsieh, Inderjit S. Dhillon:
Memory Efficient Kernel Approximation. J. Mach. Learn. Res. 18: 20:1-20:32 (2017) - [j42]Nagarajan Natarajan, Inderjit S. Dhillon, Pradeep Ravikumar, Ambuj Tewari:
Cost-Sensitive Learning with Noisy Labels. J. Mach. Learn. Res. 18: 155:1-155:33 (2017) - [j41]Prateek Jain, Ambuj Tewari, Inderjit S. Dhillon:
Partial Hard Thresholding. IEEE Trans. Inf. Theory 63(5): 3029-3038 (2017) - [c121]Hsiang-Fu Yu, Hsin-Yuan Huang, Inderjit S. Dhillon, Chih-Jen Lin:
A Unified Algorithm for One-Cass Structured Matrix Factorization with Side Information. AAAI 2017: 2845-2851 - [c120]Kai-Yang Chiang, Cho-Jui Hsieh, Inderjit S. Dhillon:
Rank Aggregation and Prediction with Item Features. AISTATS 2017: 748-756 - [c119]Kai Zhong, Ruiqi Guo, Sanjiv Kumar, Bowei Yan, David Simcha, Inderjit S. Dhillon:
Fast Classification with Binary Prototypes. AISTATS 2017: 1255-1263 - [c118]Jiong Zhang, Ian En-Hsu Yen, Pradeep Ravikumar, Inderjit S. Dhillon:
Scalable Convex Multiple Sequence Alignment via Entropy-Regularized Dual Decomposition. AISTATS 2017: 1514-1522 - [c117]Xiangru Huang, Ian En-Hsu Yen, Ruohan Zhang, Qixing Huang, Pradeep Ravikumar, Inderjit S. Dhillon:
Greedy Direction Method of Multiplier for MAP Inference of Large Output Domain. AISTATS 2017: 1550-1559 - [c116]Joyce Jiyoung Whang, Inderjit S. Dhillon:
Non-Exhaustive, Overlapping Co-Clustering. CIKM 2017: 2367-2370 - [c115]Qi Lei, Ian En-Hsu Yen, Chao-Yuan Wu, Inderjit S. Dhillon, Pradeep Ravikumar:
Doubly Greedy Primal-Dual Coordinate Descent for Sparse Empirical Risk Minimization. ICML 2017: 2034-2042 - [c114]Si Si, Huan Zhang, S. Sathiya Keerthi, Dhruv Mahajan, Inderjit S. Dhillon, Cho-Jui Hsieh:
Gradient Boosted Decision Trees for High Dimensional Sparse Output. ICML 2017: 3182-3190 - [c113]Kai Zhong, Zhao Song, Prateek Jain, Peter L. Bartlett, Inderjit S. Dhillon:
Recovery Guarantees for One-hidden-layer Neural Networks. ICML 2017: 4140-4149 - [c112]Cho-Jui Hsieh, Si Si, Inderjit S. Dhillon:
Communication-Efficient Distributed Block Minimization for Nonlinear Kernel Machines. KDD 2017: 245-254 - [c111]Ian En-Hsu Yen, Xiangru Huang, Wei Dai, Pradeep Ravikumar, Inderjit S. Dhillon, Eric P. Xing:
PPDsparse: A Parallel Primal-Dual Sparse Method for Extreme Classification. KDD 2017: 545-553 - [c110]Hsiang-Fu Yu, Cho-Jui Hsieh, Qi Lei, Inderjit S. Dhillon:
A Greedy Approach for Budgeted Maximum Inner Product Search. NIPS 2017: 5453-5462 - [i26]Qi Lei, Jinfeng Yi, Roman Vaculín, Lingfei Wu, Inderjit S. Dhillon:
Similarity Preserving Representation Learning for Time Series Analysis. CoRR abs/1702.03584 (2017) - [i25]Kai Zhong, Zhao Song, Prateek Jain, Peter L. Bartlett, Inderjit S. Dhillon:
Recovery Guarantees for One-hidden-layer Neural Networks. CoRR abs/1706.03175 (2017) - [i24]Kai Zhong, Zhao Song, Inderjit S. Dhillon:
Learning Non-overlapping Convolutional Neural Networks with Multiple Kernels. CoRR abs/1711.03440 (2017) - 2016
- [j40]Hsiang-Fu Yu, Cho-Jui Hsieh, Hyokun Yun, S. V. N. Vishwanathan, Inderjit S. Dhillon:
Nomadic Computing for Big Data Analytics. Computer 49(4): 52-60 (2016) - [j39]Berkant Savas, Inderjit S. Dhillon:
Clustered Matrix Approximation. SIAM J. Matrix Anal. Appl. 37(4): 1531-1555 (2016) - [j38]Joyce Jiyoung Whang, David F. Gleich, Inderjit S. Dhillon:
Overlapping Community Detection Using Neighborhood-Inflated Seed Expansion. IEEE Trans. Knowl. Data Eng. 28(5): 1272-1284 (2016) - [j37]Arnaud Vandaele, Nicolas Gillis, Qi Lei, Kai Zhong, Inderjit S. Dhillon:
Efficient and Non-Convex Coordinate Descent for Symmetric Nonnegative Matrix Factorization. IEEE Trans. Signal Process. 64(21): 5571-5584 (2016) - [c109]Nagarajan Natarajan, Oluwasanmi Koyejo, Pradeep Ravikumar, Inderjit S. Dhillon:
Optimal Classification with Multivariate Losses. ICML 2016: 1530-1538 - [c108]Ian En-Hsu Yen, Xin Lin, Jiong Zhang, Pradeep Ravikumar, Inderjit S. Dhillon:
A Convex Atomic-Norm Approach to Multiple Sequence Alignment and Motif Discovery. ICML 2016: 2272-2280 - [c107]Kai-Yang Chiang, Cho-Jui Hsieh, Inderjit S. Dhillon:
Robust Principal Component Analysis with Side Information. ICML 2016: 2291-2299 - [c106]David I. Inouye, Pradeep Ravikumar, Inderjit S. Dhillon:
Square Root Graphical Models: Multivariate Generalizations of Univariate Exponential Families that Permit Positive Dependencies. ICML 2016: 2445-2453 - [c105]Si Si, Cho-Jui Hsieh, Inderjit S. Dhillon:
Computationally Efficient Nyström Approximation using Fast Transforms. ICML 2016: 2655-2663 - [c104]Ian En-Hsu Yen, Xiangru Huang, Pradeep Ravikumar, Kai Zhong, Inderjit S. Dhillon:
PD-Sparse : A Primal and Dual Sparse Approach to Extreme Multiclass and Multilabel Classification. ICML 2016: 3069-3077 - [c103]Si Si, Kai-Yang Chiang, Cho-Jui Hsieh, Nikhil Rao, Inderjit S. Dhillon:
Goal-Directed Inductive Matrix Completion. KDD 2016: 1165-1174 - [c102]Hsiang-Fu Yu, Nikhil Rao, Inderjit S. Dhillon:
Temporal Regularized Matrix Factorization for High-dimensional Time Series Prediction. NIPS 2016: 847-855 - [c101]Prateek Jain, Nikhil Rao, Inderjit S. Dhillon:
Structured Sparse Regression via Greedy Hard Thresholding. NIPS 2016: 1516-1524 - [c100]Qi Lei, Kai Zhong, Inderjit S. Dhillon:
Coordinate-wise Power Method. NIPS 2016: 2056-2064 - [c99]Kai Zhong, Prateek Jain, Inderjit S. Dhillon:
Mixed Linear Regression with Multiple Components. NIPS 2016: 2190-2198 - [c98]Yang You, Xiangru Lian, Ji Liu, Hsiang-Fu Yu, Inderjit S. Dhillon, James Demmel, Cho-Jui Hsieh:
Asynchronous Parallel Greedy Coordinate Descent. NIPS 2016: 4682-4690 - [c97]Ian En-Hsu Yen, Xiangru Huang, Kai Zhong, Ruohan Zhang, Pradeep Ravikumar, Inderjit S. Dhillon:
Dual Decomposed Learning with Factorwise Oracle for Structural SVM of Large Output Domain. NIPS 2016: 5024-5032 - [c96]Yangyang Hou, Joyce Jiyoung Whang, David F. Gleich, Inderjit S. Dhillon:
Fast Multiplier Methods to Optimize Non-exhaustive, Overlapping Clustering. SDM 2016: 297-305 - [i23]Yangyang Hou, Joyce Jiyoung Whang, David F. Gleich, Inderjit S. Dhillon:
Fast Multiplier Methods to Optimize Non-exhaustive, Overlapping Clustering. CoRR abs/1602.01910 (2016) - [i22]Prateek Jain, Nikhil Rao, Inderjit S. Dhillon:
Structured Sparse Regression via Greedy Hard-Thresholding. CoRR abs/1602.06042 (2016) - [i21]Rashish Tandon, Si Si, Pradeep Ravikumar, Inderjit S. Dhillon:
Kernel Ridge Regression via Partitioning. CoRR abs/1608.01976 (2016) - [i20]Cho-Jui Hsieh, Si Si, Inderjit S. Dhillon:
Communication-Efficient Parallel Block Minimization for Kernel Machines. CoRR abs/1608.02010 (2016) - [i19]Hsiang-Fu Yu, Cho-Jui Hsieh, Qi Lei, Inderjit S. Dhillon:
A Greedy Approach for Budgeted Maximum Inner Product Search. CoRR abs/1610.03317 (2016) - 2015
- [c95]Kai Zhong, Prateek Jain, Inderjit S. Dhillon:
Efficient Matrix Sensing Using Rank-1 Gaussian Measurements. ALT 2015: 3-18 - [c94]Nagarajan Natarajan, Nikhil Rao, Inderjit S. Dhillon:
PU matrix completion with graph information. CAMSAP 2015: 37-40 - [c93]Donghyuk Shin, Suleyman Cetintas, Kuang-Chih Lee, Inderjit S. Dhillon:
Tumblr Blog Recommendation with Boosted Inductive Matrix Completion. CIKM 2015: 203-212 - [c92]Joyce Jiyoung Whang, Andrew Lenharth, Inderjit S. Dhillon, Keshav Pingali:
Scalable Data-Driven PageRank: Algorithms, System Issues, and Lessons Learned. Euro-Par 2015: 438-450 - [c91]Abhay Jha, Shubhankar Ray, Brian Seaman, Inderjit S. Dhillon:
Clustering to forecast sparse time-series data. ICDE 2015: 1388-1399 - [c90]Dohyung Park, Joe Neeman, Jin Zhang, Sujay Sanghavi, Inderjit S. Dhillon:
Preference Completion: Large-scale Collaborative Ranking from Pairwise Comparisons. ICML 2015: 1907-1916 - [c89]Cho-Jui Hsieh, Hsiang-Fu Yu, Inderjit S. Dhillon:
PASSCoDe: Parallel ASynchronous Stochastic dual Co-ordinate Descent. ICML 2015: 2370-2379 - [c88]Ian En-Hsu Yen, Xin Lin, Kai Zhong, Pradeep Ravikumar, Inderjit S. Dhillon:
A Convex Exemplar-based Approach to MAD-Bayes Dirichlet Process Mixture Models. ICML 2015: 2418-2426 - [c87]Cho-Jui Hsieh, Nagarajan Natarajan, Inderjit S. Dhillon:
PU Learning for Matrix Completion. ICML 2015: 2445-2453 - [c86]Yangyang Hou, Joyce Jiyoung Whang, David F. Gleich, Inderjit S. Dhillon:
Non-exhaustive, Overlapping Clustering via Low-Rank Semidefinite Programming. KDD 2015: 427-436 - [c85]Nikhil Rao, Hsiang-Fu Yu, Pradeep Ravikumar, Inderjit S. Dhillon:
Collaborative Filtering with Graph Information: Consistency and Scalable Methods. NIPS 2015: 2107-2115 - [c84]Ian En-Hsu Yen, Kai Zhong, Cho-Jui Hsieh, Pradeep Ravikumar, Inderjit S. Dhillon:
Sparse Linear Programming via Primal and Dual Augmented Coordinate Descent. NIPS 2015: 2368-2376 - [c83]David I. Inouye, Pradeep Ravikumar, Inderjit S. Dhillon:
Fixed-Length Poisson MRF: Adding Dependencies to the Multinomial. NIPS 2015: 3213-3221 - [c82]Oluwasanmi Koyejo, Nagarajan Natarajan, Pradeep Ravikumar, Inderjit S. Dhillon:
Consistent Multilabel Classification. NIPS 2015: 3321-3329 - [c81]Kai-Yang Chiang, Cho-Jui Hsieh, Inderjit S. Dhillon:
Matrix Completion with Noisy Side Information. NIPS 2015: 3447-3455 - [c80]Joyce Jiyoung Whang, Inderjit S. Dhillon, David F. Gleich:
Non-exhaustive, Overlapping k-means. SDM 2015: 936-944 - [c79]Hsiang-Fu Yu, Cho-Jui Hsieh, Hyokun Yun, S. V. N. Vishwanathan, Inderjit S. Dhillon:
A Scalable Asynchronous Distributed Algorithm for Topic Modeling. WWW 2015: 1340-1350 - [i18]Joyce Jiyoung Whang, David F. Gleich, Inderjit S. Dhillon:
Overlapping Community Detection Using Neighborhood-Inflated Seed Expansion. CoRR abs/1503.07439 (2015) - [i17]Cho-Jui Hsieh, Hsiang-Fu Yu, Inderjit S. Dhillon:
PASSCoDe: Parallel ASynchronous Stochastic dual Co-ordinate Descent. CoRR abs/1504.01365 (2015) - [i16]Nagarajan Natarajan, Oluwasanmi Koyejo, Pradeep Ravikumar, Inderjit S. Dhillon:
Optimal Decision-Theoretic Classification Using Non-Decomposable Performance Metrics. CoRR abs/1505.01802 (2015) - [i15]Dohyung Park, Joe Neeman, Jin Zhang, Sujay Sanghavi, Inderjit S. Dhillon:
Preference Completion: Large-scale Collaborative Ranking from Pairwise Comparisons. CoRR abs/1507.04457 (2015) - [i14]Arnaud Vandaele, Nicolas Gillis, Qi Lei, Kai Zhong, Inderjit S. Dhillon:
Coordinate Descent Methods for Symmetric Nonnegative Matrix Factorization. CoRR abs/1509.01404 (2015) - [i13]Hsiang-Fu Yu, Nikhil Rao, Inderjit S. Dhillon:
Temporal Regularized Matrix Factorization. CoRR abs/1509.08333 (2015) - 2014
- [j36]Nagarajan Natarajan, Inderjit S. Dhillon:
Inductive matrix completion for predicting gene-disease associations. Bioinform. 30(12): 60-68 (2014) - [j35]Kai-Yang Chiang, Cho-Jui Hsieh, Nagarajan Natarajan, Inderjit S. Dhillon, Ambuj Tewari:
Prediction and clustering in signed networks: a local to global perspective. J. Mach. Learn. Res. 15(1): 1177-1213 (2014) - [j34]Cho-Jui Hsieh, Mátyás A. Sustik, Inderjit S. Dhillon, Pradeep Ravikumar:
QUIC: quadratic approximation for sparse inverse covariance estimation. J. Mach. Learn. Res. 15(1): 2911-2947 (2014) - [j33]Hsiang-Fu Yu, Cho-Jui Hsieh, Si Si, Inderjit S. Dhillon:
Parallel matrix factorization for recommender systems. Knowl. Inf. Syst. 41(3): 793-819 (2014) - [j32]Hyokun Yun, Hsiang-Fu Yu, Cho-Jui Hsieh, S. V. N. Vishwanathan, Inderjit S. Dhillon:
NOMAD: Nonlocking, stOchastic Multi-machine algorithm for Asynchronous and Decentralized matrix completion. Proc. VLDB Endow. 7(11): 975-986 (2014) - [c78]Cho-Jui Hsieh, Si Si, Inderjit S. Dhillon:
A Divide-and-Conquer Solver for Kernel Support Vector Machines. ICML 2014: 566-574 - [c77]Hsiang-Fu Yu, Prateek Jain, Purushottam Kar, Inderjit S. Dhillon:
Large-scale Multi-label Learning with Missing Labels. ICML 2014: 593-601 - [c76]David I. Inouye, Pradeep Ravikumar, Inderjit S. Dhillon:
Admixture of Poisson MRFs: A Topic Model with Word Dependencies. ICML 2014: 683-691 - [c75]Si Si, Cho-Jui Hsieh, Inderjit S. Dhillon:
Memory Efficient Kernel Approximation. ICML 2014: 701-709 - [c74]Ian En-Hsu Yen, Cho-Jui Hsieh, Pradeep Ravikumar, Inderjit S. Dhillon:
Constant Nullspace Strong Convexity and Fast Convergence of Proximal Methods under High-Dimensional Settings. NIPS 2014: 1008-1016 - [c73]Cho-Jui Hsieh, Inderjit S. Dhillon, Pradeep Ravikumar, Stephen Becker, Peder A. Olsen:
QUIC & DIRTY: A Quadratic Approximation Approach for Dirty Statistical Models. NIPS 2014: 2006-2014 - [c72]Kai Zhong, Ian En-Hsu Yen, Inderjit S. Dhillon, Pradeep Ravikumar:
Proximal Quasi-Newton for Computationally Intensive L1-regularized M-estimators. NIPS 2014: 2375-2383 - [c71]Ian En-Hsu Yen, Ting-Wei Lin, Shou-De Lin, Pradeep Ravikumar, Inderjit S. Dhillon:
Sparse Random Feature Algorithm as Coordinate Descent in Hilbert Space. NIPS 2014: 2456-2464 - [c70]Oluwasanmi Koyejo, Nagarajan Natarajan, Pradeep Ravikumar, Inderjit S. Dhillon:
Consistent Binary Classification with Generalized Performance Metrics. NIPS 2014: 2744-2752 - [c69]Si Si, Donghyuk Shin, Inderjit S. Dhillon, Beresford N. Parlett:
Multi-Scale Spectral Decomposition of Massive Graphs. NIPS 2014: 2798-2806 - [c68]David I. Inouye, Pradeep Ravikumar, Inderjit S. Dhillon:
Capturing Semantically Meaningful Word Dependencies with an Admixture of Poisson MRFs. NIPS 2014: 3158-3166 - [c67]Cho-Jui Hsieh, Si Si, Inderjit S. Dhillon:
Fast Prediction for Large-Scale Kernel Machines. NIPS 2014: 3689-3697 - [i12]Cho-Jui Hsieh, Nagarajan Natarajan, Inderjit S. Dhillon:
PU Learning for Matrix Completion. CoRR abs/1411.6081 (2014) - [i11]Hsiang-Fu Yu, Cho-Jui Hsieh, Hyokun Yun, S. V. N. Vishwanathan, Inderjit S. Dhillon:
A Scalable Asynchronous Distributed Algorithm for Topic Modeling. CoRR abs/1412.4986 (2014) - 2013
- [j31]Dongmin Kim, Suvrit Sra, Inderjit S. Dhillon:
A non-monotonic method for large-scale non-negative least squares. Optim. Methods Softw. 28(5): 1012-1039 (2013) - [c66]Joyce Jiyoung Whang, David F. Gleich, Inderjit S. Dhillon:
Overlapping community detection using seed set expansion. CIKM 2013: 2099-2108 - [c65]Inderjit S. Dhillon:
Scalable Network Analysis. COMAD 2013: 4 - [c64]Joyce Jiyoung Whang, Piyush Rai, Inderjit S. Dhillon:
Stochastic Blockmodel with Cluster Overlap, Relevance Selection, and Similarity-Based Smoothing. ICDM 2013: 817-826 - [c63]Huahua Wang, Arindam Banerjee, Cho-Jui Hsieh, Pradeep Ravikumar, Inderjit S. Dhillon:
Large Scale Distributed Sparse Precision Estimation. NIPS 2013: 584-592 - [c62]Nagarajan Natarajan, Inderjit S. Dhillon, Pradeep Ravikumar, Ambuj Tewari:
Learning with Noisy Labels. NIPS 2013: 1196-1204 - [c61]Cho-Jui Hsieh, Mátyás A. Sustik, Inderjit S. Dhillon, Pradeep Ravikumar, Russell A. Poldrack:
BIG & QUIC: Sparse Inverse Covariance Estimation for a Million Variables. NIPS 2013: 3165-3173 - [c60]Nagarajan Natarajan, Donghyuk Shin, Inderjit S. Dhillon:
Which app will you use next?: collaborative filtering with interactional context. RecSys 2013: 201-208 - [e1]Inderjit S. Dhillon, Yehuda Koren, Rayid Ghani, Ted E. Senator, Paul Bradley, Rajesh Parekh, Jingrui He, Robert L. Grossman, Ramasamy Uthurusamy:
The 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2013, Chicago, IL, USA, August 11-14, 2013. ACM 2013, ISBN 978-1-4503-2174-7 [contents] - [i10]Kai-Yang Chiang, Cho-Jui Hsieh, Nagarajan Natarajan, Ambuj Tewari, Inderjit S. Dhillon:
Prediction and Clustering in Signed Networks: A Local to Global Perspective. CoRR abs/1302.5145 (2013) - [i9]Prateek Jain, Inderjit S. Dhillon:
Provable Inductive Matrix Completion. CoRR abs/1306.0626 (2013) - [i8]Cho-Jui Hsieh, Mátyás A. Sustik, Inderjit S. Dhillon, Pradeep Ravikumar:
Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation. CoRR abs/1306.3212 (2013) - [i7]Hsiang-Fu Yu, Prateek Jain, Inderjit S. Dhillon:
Large-scale Multi-label Learning with Missing Labels. CoRR abs/1307.5101 (2013) - [i6]Cho-Jui Hsieh, Si Si, Inderjit S. Dhillon:
A Divide-and-Conquer Solver for Kernel Support Vector Machines. CoRR abs/1311.0914 (2013) - [i5]Hyokun Yun, Hsiang-Fu Yu, Cho-Jui Hsieh, S. V. N. Vishwanathan, Inderjit S. Dhillon:
NOMAD: Non-locking, stOchastic Multi-machine algorithm for Asynchronous and Decentralized matrix completion. CoRR abs/1312.0193 (2013) - 2012
- [j30]Prateek Jain, Brian Kulis, Jason V. Davis, Inderjit S. Dhillon:
Metric and Kernel Learning Using a Linear Transformation. J. Mach. Learn. Res. 13: 519-547 (2012) - [j29]Mátyás A. Sustik, Inderjit S. Dhillon:
On a Zero-Finding Problem Involving the Matrix Exponential. SIAM J. Matrix Anal. Appl. 33(4): 1237-1249 (2012) - [c59]Donghyuk Shin, Si Si, Inderjit S. Dhillon:
Multi-scale link prediction. CIKM 2012: 215-224 - [c58]Kai-Yang Chiang, Joyce Jiyoung Whang, Inderjit S. Dhillon:
Scalable clustering of signed networks using balance normalized cut. CIKM 2012: 615-624 - [c57]Joyce Jiyoung Whang, Xin Sui, Inderjit S. Dhillon:
Scalable and Memory-Efficient Clustering of Large-Scale Social Networks. ICDM 2012: 705-714 - [c56]Hsiang-Fu Yu, Cho-Jui Hsieh, Si Si, Inderjit S. Dhillon:
Scalable Coordinate Descent Approaches to Parallel Matrix Factorization for Recommender Systems. ICDM 2012: 765-774 - [c55]Cho-Jui Hsieh, Kai-Yang Chiang, Inderjit S. Dhillon:
Low rank modeling of signed networks. KDD 2012: 507-515 - [c54]Xin Sui, Tsung-Hsien Lee, Joyce Jiyoung Whang, Berkant Savas, Saral Jain, Keshav Pingali, Inderjit S. Dhillon:
Parallel Clustered Low-Rank Approximation of Graphs and Its Application to Link Prediction. LCPC 2012: 76-95 - [c53]Inderjit S. Dhillon, Cho-Jui Hsieh, Mátyás A. Sustik, Pradeep Ravikumar:
Sparse inverse covariance matrix estimation using quadratic approximation. MLSLP 2012 - [c52]Cho-Jui Hsieh, Inderjit S. Dhillon, Pradeep Ravikumar, Arindam Banerjee:
A Divide-and-Conquer Method for Sparse Inverse Covariance Estimation. NIPS 2012: 2339-2347 - [c51]Han Hee Song, Berkant Savas, Tae Won Cho, Vacha Dave, Zhengdong Lu, Inderjit S. Dhillon, Yin Zhang, Lili Qiu:
Clustered embedding of massive social networks. SIGMETRICS 2012: 331-342 - [i4]Donghyuk Shin, Si Si, Inderjit S. Dhillon:
Multi-Scale Link Prediction. CoRR abs/1206.1891 (2012) - 2011
- [j28]Alexandre d'Aspremont, Francis R. Bach, Inderjit S. Dhillon, Bin Yu:
Preface. Math. Program. 127(1): 1-2 (2011) - [j27]Vishvas Vasuki, Nagarajan Natarajan, Zhengdong Lu, Berkant Savas, Inderjit S. Dhillon:
Scalable Affiliation Recommendation using Auxiliary Networks. ACM Trans. Intell. Syst. Technol. 3(1): 3:1-3:20 (2011) - [c50]Kai-Yang Chiang, Nagarajan Natarajan, Ambuj Tewari, Inderjit S. Dhillon:
Exploiting longer cycles for link prediction in signed networks. CIKM 2011: 1157-1162 - [c49]Cho-Jui Hsieh, Inderjit S. Dhillon:
Fast coordinate descent methods with variable selection for non-negative matrix factorization. KDD 2011: 1064-1072 - [c48]Ambuj Tewari, Pradeep Ravikumar, Inderjit S. Dhillon:
Greedy Algorithms for Structurally Constrained High Dimensional Problems. NIPS 2011: 882-890 - [c47]Prateek Jain, Ambuj Tewari, Inderjit S. Dhillon:
Orthogonal Matching Pursuit with Replacement. NIPS 2011: 1215-1223 - [c46]Inderjit S. Dhillon, Pradeep Ravikumar, Ambuj Tewari:
Nearest Neighbor based Greedy Coordinate Descent. NIPS 2011: 2160-2168 - [c45]Cho-Jui Hsieh, Mátyás A. Sustik, Inderjit S. Dhillon, Pradeep Ravikumar:
Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation. NIPS 2011: 2330-2338 - [c44]Berkant Savas, Inderjit S. Dhillon:
Clustered low rank approximation of graphs in information science applications. SDM 2011: 164-175 - [i3]Prateek Jain, Ambuj Tewari, Inderjit S. Dhillon:
Orthogonal Matching Pursuit with Replacement. CoRR abs/1106.2774 (2011) - 2010
- [j26]Dongmin Kim, Suvrit Sra, Inderjit S. Dhillon:
Tackling Box-Constrained Optimization via a New Projected Quasi-Newton Approach. SIAM J. Sci. Comput. 32(6): 3548-3563 (2010) - [c43]Zhengdong Lu, Berkant Savas, Wei Tang, Inderjit S. Dhillon:
Supervised Link Prediction Using Multiple Sources. ICDM 2010: 923-928 - [c42]Dongmin Kim, Suvrit Sra, Inderjit S. Dhillon:
A scalable trust-region algorithm with application to mixed-norm regression. ICML 2010: 519-526 - [c41]Prateek Jain, Raghu Meka, Inderjit S. Dhillon:
Guaranteed Rank Minimization via Singular Value Projection. NIPS 2010: 937-945 - [c40]Prateek Jain, Brian Kulis, Inderjit S. Dhillon:
Inductive Regularized Learning of Kernel Functions. NIPS 2010: 946-954 - [c39]Vishvas Vasuki, Nagarajan Natarajan, Zhengdong Lu, Inderjit S. Dhillon:
Affiliation recommendation using auxiliary networks. RecSys 2010: 103-110
2000 – 2009
- 2009
- [j25]Brian Kulis, Mátyás A. Sustik, Inderjit S. Dhillon:
Low-Rank Kernel Learning with Bregman Matrix Divergences. J. Mach. Learn. Res. 10: 341-376 (2009) - [j24]Brian Kulis, Sugato Basu, Inderjit S. Dhillon, Raymond J. Mooney:
Semi-supervised graph clustering: a kernel approach. Mach. Learn. 74(1): 1-22 (2009) - [c38]Wei Tang, Zhengdong Lu, Inderjit S. Dhillon:
Clustering with Multiple Graphs. ICDM 2009: 1016-1021 - [c37]Meghana Deodhar, Gunjan Gupta, Joydeep Ghosh, Hyuk Cho, Inderjit S. Dhillon:
A scalable framework for discovering coherent co-clusters in noisy data. ICML 2009: 241-248 - [c36]Zhengdong Lu, Prateek Jain, Inderjit S. Dhillon:
Geometry-aware metric learning. ICML 2009: 673-680 - [c35]Raghu Meka, Prateek Jain, Inderjit S. Dhillon:
Matrix Completion from Power-Law Distributed Samples. NIPS 2009: 1258-1266 - [c34]Zhengdong Lu, Deepak Agarwal, Inderjit S. Dhillon:
A spatio-temporal approach to collaborative filtering. RecSys 2009: 13-20 - [c33]Brian Kulis, Suvrit Sra, Inderjit S. Dhillon:
Convex Perturbations for Scalable Semidefinite Programming. AISTATS 2009: 296-303 - [r1]Pavel Berkhin, Inderjit S. Dhillon:
Knowledge Discovery: Clustering. Encyclopedia of Complexity and Systems Science 2009: 5051-5064 - [i2]Raghu Meka, Prateek Jain, Inderjit S. Dhillon:
Guaranteed Rank Minimization via Singular Value Projection. CoRR abs/0909.5457 (2009) - [i1]Prateek Jain, Brian Kulis, Jason V. Davis, Inderjit S. Dhillon:
Metric and Kernel Learning using a Linear Transformation. CoRR abs/0910.5932 (2009) - 2008
- [j23]Inderjit S. Dhillon, Robert W. Heath Jr., Thomas Strohmer, Joel A. Tropp:
Constructing Packings in Grassmannian Manifolds via Alternating Projection. Exp. Math. 17(1): 9-35 (2008) - [j22]Dongmin Kim, Suvrit Sra, Inderjit S. Dhillon:
Fast Projection-Based Methods for the Least Squares Nonnegative Matrix Approximation Problem. Stat. Anal. Data Min. 1(1): 38-51 (2008) - [j21]Prateek Jain, Raghu Meka, Inderjit S. Dhillon:
Simultaneous Unsupervised Learning of Disparate Clusterings. Stat. Anal. Data Min. 1(3): 195-210 (2008) - [j20]Justin Brickell, Inderjit S. Dhillon, Suvrit Sra, Joel A. Tropp:
The Metric Nearness Problem. SIAM J. Matrix Anal. Appl. 30(1): 375-396 (2008) - [j19]Hyuk Cho, Inderjit S. Dhillon:
Coclustering of Human Cancer Microarrays Using Minimum Sum-Squared Residue Coclustering. IEEE ACM Trans. Comput. Biol. Bioinform. 5(3): 385-400 (2008) - [c32]Meghana Deodhar, Joydeep Ghosh, Gunjan Gupta, Hyuk Cho, Inderjit S. Dhillon:
Hunting for Coherent Co-clusters in High Dimensional and Noisy Datasets. ICDM Workshops 2008: 654-663 - [c31]Raghu Meka, Prateek Jain, Constantine Caramanis, Inderjit S. Dhillon:
Rank minimization via online learning. ICML 2008: 656-663 - [c30]Jason V. Davis, Inderjit S. Dhillon:
Structured metric learning for high dimensional problems. KDD 2008: 195-203 - [c29]Prateek Jain, Brian Kulis, Inderjit S. Dhillon, Kristen Grauman:
Online Metric Learning and Fast Similarity Search. NIPS 2008: 761-768 - [c28]Prateek Jain, Raghu Meka, Inderjit S. Dhillon:
Simultaneous Unsupervised Learning of Disparate Clusterings. SDM 2008: 858-869 - 2007
- [j18]Arindam Banerjee, Inderjit S. Dhillon, Joydeep Ghosh, Srujana Merugu, Dharmendra S. Modha:
A Generalized Maximum Entropy Approach to Bregman Co-clustering and Matrix Approximation. J. Mach. Learn. Res. 8: 1919-1986 (2007) - [j17]Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis:
Weighted Graph Cuts without Eigenvectors A Multilevel Approach. IEEE Trans. Pattern Anal. Mach. Intell. 29(11): 1944-1957 (2007) - [j16]Inderjit S. Dhillon, Joel A. Tropp:
Matrix Nearness Problems with Bregman Divergences. SIAM J. Matrix Anal. Appl. 29(4): 1120-1146 (2007) - [c27]Jason V. Davis, Brian Kulis, Prateek Jain, Suvrit Sra, Inderjit S. Dhillon:
Information-theoretic metric learning. ICML 2007: 209-216 - [c26]Dongmin Kim, Suvrit Sra, Inderjit S. Dhillon:
Fast Newton-type Methods for the Least Squares Nonnegative Matrix Approximation Problem. SDM 2007: 343-354 - 2006
- [j15]Inderjit S. Dhillon, Beresford N. Parlett, Christof Vömel:
The design and implementation of the MRRR algorithm. ACM Trans. Math. Softw. 32(4): 533-560 (2006) - [c25]Brian Kulis, Mátyás A. Sustik, Inderjit S. Dhillon:
Learning low-rank kernel matrices. ICML 2006: 505-512 - [c24]Justin Brickell, Inderjit S. Dhillon, Dharmendra S. Modha:
Adaptive Website Design Using Caching Algorithms. WEBKDD 2006: 1-20 - [c23]Jason V. Davis, Inderjit S. Dhillon:
Estimating the global pagerank of web communities. KDD 2006: 116-125 - [c22]Jason V. Davis, Inderjit S. Dhillon:
Differential Entropic Clustering of Multivariate Gaussians. NIPS 2006: 337-344 - [p1]Marc Teboulle, Pavel Berkhin, Inderjit S. Dhillon, Yuqiang Guan, Jacob Kogan:
Clustering with Entropy-Like k-Means Algorithms. Grouping Multidimensional Data 2006: 127-160 - 2005
- [j14]Arindam Banerjee, Inderjit S. Dhillon, Joydeep Ghosh, Suvrit Sra:
Clustering on the Unit Hypersphere using von Mises-Fisher Distributions. J. Mach. Learn. Res. 6: 1345-1382 (2005) - [j13]Arindam Banerjee, Srujana Merugu, Inderjit S. Dhillon, Joydeep Ghosh:
Clustering with Bregman Divergences. J. Mach. Learn. Res. 6: 1705-1749 (2005) - [j12]Inderjit S. Dhillon, Robert W. Heath Jr., Mátyás A. Sustik, Joel A. Tropp:
Generalized Finite Algorithms for Constructing Hermitian Matrices with Prescribed Diagonal and Spectrum. SIAM J. Matrix Anal. Appl. 27(1): 61-71 (2005) - [j11]Paolo Bientinesi, Inderjit S. Dhillon, Robert A. van de Geijn:
A Parallel Eigensolver for Dense Symmetric Matrices Based on Multiple Relatively Robust Representations. SIAM J. Sci. Comput. 27(1): 43-66 (2005) - [j10]Inderjit S. Dhillon, Beresford N. Parlett, Christof Vömel:
Glued Matrices and the MRRR Algorithm. SIAM J. Sci. Comput. 27(2): 496-510 (2005) - [j9]Joel A. Tropp, Inderjit S. Dhillon, Robert W. Heath Jr., Thomas Strohmer:
Designing structured tight frames via an alternating projection method. IEEE Trans. Inf. Theory 51(1): 188-209 (2005) - [c21]Brian Kulis, Sugato Basu, Inderjit S. Dhillon, Raymond J. Mooney:
Semi-supervised graph clustering: a kernel approach. ICML 2005: 457-464 - [c20]Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis:
A fast kernel-based multilevel algorithm for graph clustering. KDD 2005: 629-634 - [c19]Inderjit S. Dhillon, Suvrit Sra:
Generalized Nonnegative Matrix Approximations with Bregman Divergences. NIPS 2005: 283-290 - 2004
- [j8]Joel A. Tropp, Inderjit S. Dhillon, Robert W. Heath Jr.:
Finite-Step Algorithms for Constructing Optimal CDMA Signature Sequences. IEEE Trans. Inf. Theory 50(11): 2916-2921 (2004) - [c18]Arindam Banerjee, Inderjit S. Dhillon, Joydeep Ghosh, Srujana Merugu:
An information theoretic analysis of maximum likelihood mixture estimation for exponential families. ICML 2004 - [c17]Arindam Banerjee, Inderjit S. Dhillon, Joydeep Ghosh, Srujana Merugu, Dharmendra S. Modha:
A generalized maximum entropy approach to bregman co-clustering and matrix approximation. KDD 2004: 509-514 - [c16]Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis:
Kernel k-means: spectral clustering and normalized cuts. KDD 2004: 551-556 - [c15]Inderjit S. Dhillon, Suvrit Sra, Joel A. Tropp:
Triangle Fixing Algorithms for the Metric Nearness Problem. NIPS 2004: 361-368 - [c14]Hyuk Cho, Inderjit S. Dhillon, Yuqiang Guan, Suvrit Sra:
Minimum Sum-Squared Residue Co-Clustering of Gene Expression Data. SDM 2004: 114-125 - [c13]Arindam Banerjee, Srujana Merugu, Inderjit S. Dhillon, Joydeep Ghosh:
Clustering with Bregman Divergences. SDM 2004: 234-245 - 2003
- [j7]Inderjit S. Dhillon, Edward M. Marcotte, Usman Roshan:
Diametrical clustering for identifying anti-correlated gene clusters. Bioinform. 19(13): 1612-1619 (2003) - [j6]Inderjit S. Dhillon, Subramanyam Mallela, Rahul Kumar:
A Divisive Information-Theoretic Feature Clustering Algorithm for Text Classification. J. Mach. Learn. Res. 3: 1265-1287 (2003) - [j5]Inderjit S. Dhillon, Beresford N. Parlett:
Orthogonal Eigenvectors and Relative Gaps. SIAM J. Matrix Anal. Appl. 25(3): 858-899 (2003) - [c12]Inderjit S. Dhillon, Yuqiang Guan:
Information Theoretic Clustering of Sparse Co-Occurrence Data. ICDM 2003: 517-520 - [c11]Arindam Banerjee, Inderjit S. Dhillon, Joydeep Ghosh, Suvrit Sra:
Generative model-based clustering of directional data. KDD 2003: 19-28 - [c10]Inderjit S. Dhillon, Subramanyam Mallela, Dharmendra S. Modha:
Information-theoretic co-clustering. KDD 2003: 89-98 - 2002
- [j4]Inderjit S. Dhillon, Dharmendra S. Modha, W. Scott Spangler:
Class visualization of high-dimensional data with applications. Comput. Stat. Data Anal. 41(1): 59-90 (2002) - [c9]Inderjit S. Dhillon, Yuqiang Guan, Jacob Kogan:
Iterative Clustering of High Dimensional Text Data Augmented by Local Search. ICDM 2002: 131-138 - [c8]Inderjit S. Dhillon, Subramanyam Mallela, Rahul Kumar:
Enhanced word clustering for hierarchical text classification. KDD 2002: 191-200 - 2001
- [j3]Inderjit S. Dhillon, Dharmendra S. Modha:
Concept Decompositions for Large Sparse Text Data Using Clustering. Mach. Learn. 42(1/2): 143-175 (2001) - [c7]Inderjit S. Dhillon:
Co-clustering documents and words using bipartite spectral graph partitioning. KDD 2001: 269-274
1990 – 1999
- 1999
- [c6]Inderjit S. Dhillon, Dharmendra S. Modha:
A Data-Clustering Algorithm on Distributed Memory Multiprocessors. Large-Scale Parallel Data Mining 1999: 245-260 - 1998
- [j2]Inderjit S. Dhillon:
Reliable Computation of the Condition Number of a Tridiagonal Matrix in O(n) Time. SIAM J. Matrix Anal. Appl. 19(3): 776-796 (1998) - 1997
- [j1]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:
Practical Experience in the Numerical Dangers of Heterogeneous Computing. ACM Trans. Math. Softw. 23(2): 133-147 (1997) - [c5]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:
ScaLAPACK: A Linear Algebra Library for Message-Passing Computers. PP 1997 - [c4]Inderjit S. Dhillon, George Fann, Beresford N. Parlett:
Application of a New Algorithm for the Symmetric Eigenproblem to Computational Quantum Chemistry. PP 1997 - 1996
- [c3]Andrew J. Cleary, James Demmel, Inderjit S. Dhillon, Jack J. Dongarra, Sven Hammarling, Antoine Petitet, H. Ren, Ken Stanley, R. Clinton Whaley:
Practical Experience in the Dangers of Heterogeneous Computing. PARA 1996: 57-64 - [c2]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:
ScaLAPACK: A Portable Linear Algebra Library for Distributed Memory Computers - Design Issues and Performance. SC 1996: 5 - 1995
- [c1]Jaeyoung Choi, James Demmel, Inderjit S. Dhillon, Jack J. Dongarra, Susan Ostrouchov, Antoine Petitet, Ken Stanley, David W. Walker, R. Clinton Whaley:
ScaLAPACK: A Portable Linear Algebra Library for Distributed Memory Computers - Design Issues and Performance. PARA 1995: 95-106
Coauthor Index
[c168] [c166] [c164] [i78] [i77] [c162] [c161] [c160] [i73] [i72] [c158] [c156] [c155] [c153] [i67] [i66] [i65] [c143] [c142] [i56] [i52] [i51] [c141] [i50] [i49] [i43] [c135] [c133] [i40] [j44] [c125] [i30] [j43] [c120] [c114] [c112] [c110] [j40] [c107] [c105] [c103] [c98] [i20] [i19] [c89] [c87] [c84] [c81] [c79] [i17] [j35] [j34] [j33] [j32] [c78] [c75] [c74] [c73] [c67] [i12] [i11] [c63] [c61] [i10] [i8] [i6] [i5] [c56] [c55] [c53] [c52] [c49] [c45]
[j49] [j48] [c160] [j47] [c158] [c155] [c153] [c150] [i71] [i67] [i66] [c146] [c144] [c143] [c142] [i60] [i57] [i56] [i55] [i54] [i52] [i51] [c141] [c140] [c139] [i49] [i48] [i45] [c136] [c135] [c130] [c129] [i38] [i37] [i36] [i33] [c121] [c110] [j40] [c102] [c98] [i19] [c89] [c85] [c79] [i17] [i13] [j33] [j32] [c77] [i11] [i7] [i5] [c56]
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