Sanghavi, Sujay

69 publications

ICLR 2025 Enhancing Language Model Agents Using Diversity of Thoughts Vijay Lingam, Behrooz Omidvar Tehrani, Sujay Sanghavi, Gaurav Gupta, Sayan Ghosh, Linbo Liu, Jun Huan, Anoop Deoras

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

ICLR 2025 Infilling Score: A Pretraining Data Detection Algorithm for Large Language Models Negin Raoof, Litu Rout, Giannis Daras, Sujay Sanghavi, Constantine Caramanis, Sanjay Shakkottai, Alex Dimakis

ICML 2025 Learning Mixtures of Experts with EM: A Mirror Descent Perspective Quentin Fruytier, Aryan Mokhtari, Sujay Sanghavi

ICML 2025 Retraining with Predicted Hard Labels Provably Increases Model Accuracy Rudrajit Das, Inderjit S Dhillon, Alessandro Epasto, Adel Javanmard, Jieming Mao, Vahab Mirrokni, Sujay Sanghavi, Peilin Zhong

NeurIPS 2025 Understanding Contrastive Learning via Gaussian Mixture Models Parikshit Bansal, Ali Kavis, Sujay Sanghavi

ICML 2025 Upweighting Easy Samples in Fine-Tuning Mitigates Forgetting Sunny Sanyal, Hayden Prairie, Rudrajit Das, Ali Kavis, Sujay Sanghavi

NeurIPS 2024 Adaptive and Optimal Second-Order Optimistic Methods for Minimax Optimization Ruichen Jiang, Ali Kavis, Qiujiang Jin, Sujay Sanghavi, Aryan Mokhtari

NeurIPS 2024 DataComp-LM: In Search of the Next Generation of Training Sets for Language Models Jeffrey Li, Alex Fang, Georgios Smyrnis, Maor Ivgi, Matt Jordan, Samir Gadre, Hritik Bansal, Etash Guha, Sedrick Keh, Kushal Arora, Saurabh Garg, Rui Xin, Niklas Muennighoff, Reinhard Heckel, Jean Mercat, Mayee Chen, Suchin Gururangan, Mitchell Wortsman, Alon Albalak, Yonatan Bitton, Marianna Nezhurina, Amro Abbas, Cheng-Yu Hsieh, Dhruba Ghosh, Josh Gardner, Maciej Kilian, Hanlin Zhang, Rulin Shao, Sarah Pratt, Sunny Sanyal, Gabriel Ilharco, Giannis Daras, Kalyani Marathe, Aaron Gokaslan, Jieyu Zhang, Khyathi Chandu, Thao Nguyen, Igor Vasiljevic, Sham Kakade, Shuran Song, Sujay Sanghavi, Fartash Faghri, Sewoong Oh, Luke Zettlemoyer, Kyle Lo, Alaaeldin El-Nouby, Hadi Pouransari, Alexander Toshev, Stephanie Wang, Dirk Groeneveld, Luca Soldaini, Pang Wei Koh, Jenia Jitsev, Thomas Kollar, Alexandros G. Dimakis, Yair Carmon, Achal Dave, Ludwig Schmidt, Vaishaal Shankar

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

ICML 2024 Improving Computational Complexity in Statistical Models with Local Curvature Information Pedram Akbarian, Tongzheng Ren, Jiacheng Zhuo, Sujay Sanghavi, Nhat Ho

NeurIPS 2024 In-Context Learning with Transformers: SoftMax Attention Adapts to Function Lipschitzness Liam Collins, Advait Parulekar, Aryan Mokhtari, Sujay Sanghavi, Sanjay Shakkottai

TMLR 2024 Pretrained Deep Models Outperform GBDTs in Learning-to-Rank Under Label Scarcity Charlie Hou, Kiran Koshy Thekumparampil, Michael Shavlovsky, Giulia Fanti, Yesh Dattatreya, Sujay Sanghavi

ICMLW 2024 Pretrained Deep Models Outperform GBDTs in Learning-to-Rank Under Label Scarcity Charlie Hou, Kiran Koshy Thekumparampil, Michael Shavlovsky, Giulia Fanti, Sujay Sanghavi

NeurIPS 2024 SVFT: Parameter-Efficient Fine-Tuning with Singular Vectors Vijay Lingam, Atula Tejaswi, Aditya Vavre, Aneesh Shetty, Gautham Krishna Gudur, Joydeep Ghosh, Alex Dimakis, Eunsol Choi, Aleksandar Bojchevski, Sujay Sanghavi

ICMLW 2024 SVFT: Parameter-Efficient Fine-Tuning with Singular Vectors Vijay Lingam, Atula Tejaswi Neerkaje, Aditya Vavre, Aneesh Shetty, Gautham Krishna Gudur, Joydeep Ghosh, Alex Dimakis, Eunsol Choi, Aleksandar Bojchevski, Sujay Sanghavi

ICMLW 2024 SVFT: Parameter-Efficient Fine-Tuning with Singular Vectors Vijay Lingam, Atula Tejaswi Neerkaje, Aditya Vavre, Aneesh Shetty, Gautham Krishna Gudur, Joydeep Ghosh, Eunsol Choi, Alex Dimakis, Aleksandar Bojchevski, Sujay Sanghavi

NeurIPSW 2024 SVFT: Parameter-Efficient Fine-Tuning with Singular Vectors Vijay Lingam, Atula Tejaswi, Aditya Vavre, Aneesh Shetty, Gautham Krishna Gudur, Joydeep Ghosh, Alex Dimakis, Eunsol Choi, Aleksandar Bojchevski, Sujay Sanghavi

ICML 2024 Time Weaver: A Conditional Time Series Generation Model Sai Shankar Narasimhan, Shubhankar Agarwal, Oguzhan Akcin, Sujay Sanghavi, Sandeep P. Chinchali

ICML 2024 Understanding the Training Speedup from Sampling with Approximate Losses Rudrajit Das, Xi Chen, Bertram Ieong, Parikshit Bansal, Sujay Sanghavi

ICML 2023 Beyond Uniform Lipschitz Condition in Differentially Private Optimization Rudrajit Das, Satyen Kale, Zheng Xu, Tong Zhang, Sujay Sanghavi

ICMLW 2023 Contextual Set Selection Under Human Feedback with Model Misspecification Shuo Yang, Rajat Sen, Sujay Sanghavi

NeurIPSW 2023 Early Weight Averaging Meets High Learning Rates for LLM Pre-Training Sunny Sanyal, Atula Tejaswi Neerkaje, Jean Kaddour, Abhishek Kumar, Sujay Sanghavi

NeurIPS 2023 Finite-Time Logarithmic Bayes Regret Upper Bounds Alexia Atsidakou, Branislav Kveton, Sumeet Katariya, Constantine Caramanis, Sujay Sanghavi

ICLR 2023 Latent Variable Representation for Reinforcement Learning Tongzheng Ren, Chenjun Xiao, Tianjun Zhang, Na Li, Zhaoran Wang, Sujay Sanghavi, Dale Schuurmans, Bo Dai

ICMLW 2023 Pretrained Deep Models Outperform GBDTs in Learning-to-Rank Under Label Scarcity Charlie Hou, Kiran Koshy Thekumparampil, Michael Shavlovsky, Giulia Fanti, Yesh Dattatreya, Sujay Sanghavi

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

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

ICML 2023 Understanding Self-Distillation in the Presence of Label Noise Rudrajit Das, Sujay Sanghavi

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

AISTATS 2022 Towards Statistical and Computational Complexities of Polyak Step Size Gradient Descent Tongzheng Ren, Fuheng Cui, Alexia Atsidakou, Sujay Sanghavi, Nhat Ho

ICML 2022 Asymptotically-Optimal Gaussian Bandits with Side Observations Alexia Atsidakou, Orestis Papadigenopoulos, Constantine Caramanis, Sujay Sanghavi, Sanjay Shakkottai

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

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

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

NeurIPS 2022 Minimax Regret for Cascading Bandits Daniel Vial, Sujay Sanghavi, Sanjay Shakkottai, R. Srikant

NeurIPS 2022 Toward Understanding Privileged Features Distillation in Learning-to-Rank Shuo Yang, Sujay Sanghavi, Holakou Rahmanian, Jan Bakus, S. V. N. Vishwanathan

NeurIPS 2021 Nearly Horizon-Free Offline Reinforcement Learning Tongzheng Ren, Jialian Li, Bo Dai, Simon S Du, Sujay Sanghavi

AISTATS 2020 Choosing the Sample with Lowest Loss Makes SGD Robust Vatsal Shah, Xiaoxia Wu, Sujay Sanghavi

ICML 2020 Extreme Multi-Label Classification from Aggregated Labels Yanyao Shen, Hsiang-Fu Yu, Sujay Sanghavi, Inderjit Dhillon

NeurIPS 2019 Blocking Bandits Soumya Basu, Rajat Sen, Sujay Sanghavi, Sanjay Shakkottai

NeurIPS 2019 Interaction Hard Thresholding: Consistent Sparse Quadratic Regression in Sub-Quadratic Time and Space Shuo Yang, Yanyao Shen, Sujay Sanghavi

NeurIPS 2019 Iterative Least Trimmed Squares for Mixed Linear Regression Yanyao Shen, Sujay Sanghavi

NeurIPS 2019 Learning Distributions Generated by One-Layer ReLU Networks Shanshan Wu, Alexandros G Dimakis, Sujay Sanghavi

ICML 2019 Learning a Compressed Sensing Measurement Matrix via Gradient Unrolling Shanshan Wu, Alex Dimakis, Sujay Sanghavi, Felix Yu, Daniel Holtmann-Rice, Dmitry Storcheus, Afshin Rostamizadeh, Sanjiv Kumar

ICML 2019 Learning with Bad Training Data via Iterative Trimmed Loss Minimization Yanyao Shen, Sujay Sanghavi

NeurIPS 2019 Sparse Logistic Regression Learns All Discrete Pairwise Graphical Models Shanshan Wu, Sujay Sanghavi, Alexandros G Dimakis

AISTATS 2017 Non-Square Matrix Sensing Without Spurious Local Minima via the Burer-Monteiro Approach Dohyung Park, Anastasios Kyrillidis, Constantine Caramanis, Sujay Sanghavi

COLT 2016 Dropping Convexity for Faster Semi-Definite Optimization Srinadh Bhojanapalli, Anastasios Kyrillidis, Sujay Sanghavi

NeurIPS 2016 Normalized Spectral mAP Synchronization Yanyao Shen, Qixing Huang, Nati Srebro, Sujay Sanghavi

NeurIPS 2016 Single Pass PCA of Matrix Products Shanshan Wu, Srinadh Bhojanapalli, Sujay Sanghavi, Alexandros G Dimakis

JMLR 2015 Completing Any Low-Rank Matrix, Provably Yudong Chen, Srinadh Bhojanapalli, Sujay Sanghavi, Rachel Ward

NeurIPS 2015 Convergence Rates of Active Learning for Maximum Likelihood Estimation Kamalika Chaudhuri, Sham M. Kakade, Praneeth Netrapalli, Sujay Sanghavi

ICML 2015 Preference Completion: Large-Scale Collaborative Ranking from Pairwise Comparisons Dohyung Park, Joe Neeman, Jin Zhang, Sujay Sanghavi, Inderjit Dhillon

ICML 2014 Alternating Minimization for Mixed Linear Regression Xinyang Yi, Constantine Caramanis, Sujay Sanghavi

JMLR 2014 Clustering Partially Observed Graphs via Convex Optimization Yudong Chen, Ali Jalali, Sujay Sanghavi, Huan Xu

ICML 2014 Coherent Matrix Completion Yudong Chen, Srinadh Bhojanapalli, Sujay Sanghavi, Rachel Ward

NeurIPS 2014 Greedy Subspace Clustering Dohyung Park, Constantine Caramanis, Sujay Sanghavi

NeurIPS 2014 Non-Convex Robust PCA Praneeth Netrapalli, U N Niranjan, Sujay Sanghavi, Animashree Anandkumar, Prateek Jain

NeurIPS 2013 Phase Retrieval Using Alternating Minimization Praneeth Netrapalli, Prateek Jain, Sujay Sanghavi

NeurIPS 2012 Clustering Sparse Graphs Yudong Chen, Sujay Sanghavi, Huan Xu

ICML 2012 Learning the Dependence Graph of Time Series with Latent Factors Ali Jalali, Sujay Sanghavi

ICML 2011 Clustering Partially Observed Graphs via Convex Optimization Ali Jalali, Yudong Chen, Sujay Sanghavi, Huan Xu

AISTATS 2011 On Learning Discrete Graphical Models Using Group-Sparse Regularization Ali Jalali, Pradeep Ravikumar, Vishvas Vasuki, Sujay Sanghavi

ICML 2011 Robust Matrix Completion and Corrupted Columns Yudong Chen, Huan Xu, Constantine Caramanis, Sujay Sanghavi

NeurIPS 2010 A Dirty Model for Multi-Task Learning Ali Jalali, Sujay Sanghavi, Chao Ruan, Pradeep K. Ravikumar

NeurIPS 2010 Robust PCA via Outlier Pursuit Huan Xu, Constantine Caramanis, Sujay Sanghavi

NeurIPS 2007 Linear Programming Analysis of Loopy Belief Propagation for Weighted Matching Sujay Sanghavi, Dmitry Malioutov, Alan S. Willsky

NeurIPS 2007 Message Passing for Max-Weight Independent Set Sujay Sanghavi, Devavrat Shah, Alan S. Willsky