Sujay Sanghavi

217 papers A* 48A 9B 4Misc 3Journal 126Unranked 26

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	EntRGi: Entropy Aware Reward Guidance for Diffusion Language Models. CoRR Atula Tejaswi, Litu Rout, Constantine Caramanis, Sanjay Shakkottai, Sujay Sanghavi
2026	J	`jnl`	When Attention Collapses: How Degenerate Layers in LLMs Enable Smaller, Stronger Models. Trans. Mach. Learn. Res. Sunny Sanyal, Ravid Shwartz-Ziv, Alex Dimakis, Sujay Sanghavi
2025	J	`jnl`	Asymptotically-Optimal Gaussian Bandits with Side Observations. CoRR Alexia Atsidakou, Orestis Papadigenopoulos, Constantine Caramanis, Sujay Sanghavi, Sanjay Shakkottai
2025	J	`jnl`	Context-Free Synthetic Data Mitigates Forgetting. CoRR Parikshit Bansal, Sujay Sanghavi
2025	J	`jnl`	Enabling Approximate Joint Sampling in Diffusion LMs. CoRR Parikshit Bansal, Sujay Sanghavi
2025	A*	`conf`	Enhancing Language Model Agents using Diversity of Thoughts. ICLR Vijay Lingam, Behrooz Omidvar-Tehrani, Sujay Sanghavi, Gaurav Gupta, Sayan Ghosh, Linbo Liu, Jun Huan, Anoop Deoras
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	J	`jnl`	HiSpec: Hierarchical Speculative Decoding for LLMs. CoRR Avinash Kumar, Sujay Sanghavi, Poulami Das
2025	A*	`conf`	Infilling Score: A Pretraining Data Detection Algorithm for Large Language Models. ICLR Negin Raoof, Litu Rout, Giannis Daras, Sujay Sanghavi, Constantine Caramanis, Sanjay Shakkottai, Alex Dimakis
2025	—	`conf`	InfoPO: On Mutual Information Maximization for Large Language Model Alignment. NAACL (Long Papers) Teng Xiao, Zhen Ge, Sujay Sanghavi, Tian Wang, Julian Katz-Samuels, Marc Versage, Qingjun Cui, Trishul Chilimbi
2025	J	`jnl`	InfoPO: On Mutual Information Maximization for Large Language Model Alignment. CoRR Teng Xiao, Zhen Ge, Sujay Sanghavi, Tian Wang, Julian Katz-Samuels, Marc Versage, Qingjun Cui, Trishul Chilimbi
2025	A*	`conf`	Learning Mixtures of Experts with EM: A Mirror Descent Perspective. ICML Quentin Fruytier, Aryan Mokhtari, Sujay Sanghavi
2025	J	`jnl`	MURPHY: Multi-Turn GRPO for Self Correcting Code Generation. CoRR Chanakya Ekbote, Vijay Lingam, Behrooz Omidvar-Tehrani, Jun Huan, Sujay Sanghavi, Anoop Deoras, Stefano Soatto
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`	SFT Doesn't Always Hurt General Capabilities: Revisiting Domain-Specific Fine-Tuning in LLMs. CoRR Jiacheng Lin, Zhongruo Wang, Kun Qian, Tian Wang, Arvind Srinivasan, Hansi Zeng, Ruochen Jiao, Xie Zhou, Jiri Gesi, Dakuo Wang, Yufan Guo, Kai Zhong, Weiqi Zhang, Sujay Sanghavi, Changyou Chen, Hyokun Yun, Lihong Li
2025	J	`jnl`	Sculpting Latent Spaces With MMD: Disentanglement With Programmable Priors. CoRR Quentin Fruytier, Akshay Malhotra, Shahab Hamidi-Rad, Aditya Sant, Aryan Mokhtari, Sujay Sanghavi
2025	A*	`conf`	Upweighting Easy Samples in Fine-Tuning Mitigates Forgetting. ICML Sunny Sanyal, Hayden Prairie, Rudrajit Das, Ali Kavis, Sujay Sanghavi
2025	J	`jnl`	Upweighting Easy Samples in Fine-Tuning Mitigates Forgetting. CoRR Sunny Sanyal, Hayden Prairie, Rudrajit Das, Ali Kavis, Sujay Sanghavi
2024	A*	`conf`	Adaptive and Optimal Second-order Optimistic Methods for Minimax Optimization. NeurIPS Ruichen Jiang, Ali Kavis, Qiujiang Jin, Sujay Sanghavi, Aryan Mokhtari
2024	J	`jnl`	Adaptive and Optimal Second-order Optimistic Methods for Minimax Optimization. CoRR Ruichen Jiang, Ali Kavis, Qiujiang Jin, Sujay Sanghavi, Aryan Mokhtari
2024	J	`jnl`	Contrastive Approach to Prior Free Positive Unlabeled Learning. CoRR Anish Acharya, Sujay Sanghavi
2024	A*	`conf`	DataComp-LM: In search of the next generation of training sets for language models. NeurIPS Jeffrey Li, Alex Fang, Georgios Smyrnis, Maor Ivgi, Matt Jordan, Samir Yitzhak Gadre, Hritik Bansal, Etash Kumar Guha, Sedrick Scott Keh, Kushal Arora, Saurabh Garg, Rui Xin, Niklas Muennighoff, Reinhard Heckel, Jean Mercat, Mayee F. 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 M. Pratt, Sunny Sanyal, Gabriel Ilharco, Giannis Daras, Kalyani Marathe, Aaron Gokaslan, Jieyu Zhang, Khyathi Raghavi Chandu, Thao Nguyen, Igor Vasiljevic, Sham M. 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, Alex Dimakis, Yair Carmon, Achal Dave, Ludwig Schmidt, Vaishaal Shankar
2024	J	`jnl`	DataComp-LM: In search of the next generation of training sets for language models. CoRR Jeffrey Li, Alex Fang, Georgios Smyrnis, Maor Ivgi, Matt Jordan, Samir Yitzhak Gadre, Hritik Bansal, Etash Kumar Guha, Sedrick Keh, Kushal Arora, Saurabh Garg, Rui Xin, Niklas Muennighoff, Reinhard Heckel, Jean Mercat, Mayee F. 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 M. Pratt, Sunny Sanyal, Gabriel Ilharco, Giannis Daras, Kalyani Marathe, Aaron Gokaslan, Jieyu Zhang, Khyathi Raghavi Chandu, Thao Nguyen, Igor Vasiljevic, Sham M. 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
2024	J	`jnl`	Geometric Median (GM) Matching for Robust Data Pruning. CoRR Anish Acharya, Inderjit S. Dhillon, Sujay Sanghavi
2024	A*	`conf`	Improving Computational Complexity in Statistical Models with Local Curvature Information. ICML Pedram Akbarian, Tongzheng Ren, Jiacheng Zhuo, Sujay Sanghavi, Nhat Ho
2024	A*	`conf`	In-Context Learning with Transformers: Softmax Attention Adapts to Function Lipschitzness. NeurIPS Liam Collins, Advait Parulekar, Aryan Mokhtari, Sujay Sanghavi, Sanjay Shakkottai
2024	J	`jnl`	In-Context Learning with Transformers: Softmax Attention Adapts to Function Lipschitzness. CoRR Liam Collins, Advait Parulekar, Aryan Mokhtari, Sujay Sanghavi, Sanjay Shakkottai
2024	J	`jnl`	Learning Mixtures of Experts with EM. CoRR Quentin Fruytier, Aryan Mokhtari, Sujay Sanghavi
2024	J	`jnl`	Pre-training Small Base LMs with Fewer Tokens. CoRR Sunny Sanyal, Sujay Sanghavi, Alexandros G. Dimakis
2024	J	`jnl`	Pretrained deep models outperform GBDTs in Learning-To-Rank under label scarcity. Trans. Mach. Learn. Res. Charlie Hou, Kiran Koshy Thekumparampil, Michael Shavlovsky, Giulia Fanti, Yesh Dattatreya, Sujay Sanghavi
2024	J	`jnl`	RARe: Retrieval Augmented Retrieval with In-Context Examples. CoRR Atula Tejaswi, Yoonsang Lee, Sujay Sanghavi, Eunsol Choi
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	A*	`conf`	SVFT: Parameter-Efficient Fine-Tuning with Singular Vectors. NeurIPS Vijay Lingam, Atula Neerkaje, Aditya Vavre, Aneesh Shetty, Gautham Krishna Gudur, Joydeep Ghosh, Eunsol Choi, Alex Dimakis, Aleksandar Bojchevski, Sujay Sanghavi
2024	J	`jnl`	SVFT: Parameter-Efficient Fine-Tuning with Singular Vectors. CoRR Vijay Lingam, Atula Tejaswi, Aditya Vavre, Aneesh Shetty, Gautham Krishna Gudur, Joydeep Ghosh, Alex Dimakis, Eunsol Choi, Aleksandar Bojchevski, Sujay Sanghavi
2024	A*	`conf`	Time Weaver: A Conditional Time Series Generation Model. ICML Sai Shankar Narasimhan, Shubhankar Agarwal, Oguzhan Akcin, Sujay Sanghavi, Sandeep P. Chinchali
2024	J	`jnl`	Time Weaver: A Conditional Time Series Generation Model. CoRR Sai Shankar Narasimhan, Shubhankar Agarwal, Oguzhan Akcin, Sujay Sanghavi, Sandeep Chinchali
2024	J	`jnl`	Towards Quantifying the Preconditioning Effect of Adam. CoRR Rudrajit Das, Naman Agarwal, Sujay Sanghavi, Inderjit S. Dhillon
2024	J	`jnl`	Understanding Contrastive Learning via Gaussian Mixture Models. CoRR Parikshit Bansal, Ali Kavis, Sujay Sanghavi
2024	A*	`conf`	Understanding the Training Speedup from Sampling with Approximate Losses. ICML Rudrajit Das, Xi Chen, Bertram Ieong, Parikshit Bansal, Sujay Sanghavi
2024	J	`jnl`	Understanding the Training Speedup from Sampling with Approximate Losses. CoRR Rudrajit Das, Xi Chen, Bertram Ieong, Parikshit Bansal, Sujay Sanghavi
2023	A*	`conf`	Beyond Uniform Lipschitz Condition in Differentially Private Optimization. ICML Rudrajit Das, Satyen Kale, Zheng Xu, Tong Zhang, Sujay Sanghavi
2023	A*	`conf`	Latent Variable Representation for Reinforcement Learning. ICLR Tongzheng Ren, Chenjun Xiao, Tianjun Zhang, Na Li, Zhaoran Wang, Sujay Sanghavi, Dale Schuurmans, Bo Dai
2023	A*	`conf`	Logarithmic Bayes Regret Bounds. NeurIPS Alexia Atsidakou, Branislav Kveton, Sumeet Katariya, Constantine Caramanis, Sujay Sanghavi
2023	J	`jnl`	Logarithmic Bayes Regret Bounds. CoRR Alexia Atsidakou, Branislav Kveton, Sumeet Katariya, Constantine Caramanis, Sujay Sanghavi
2023	J	`jnl`	Pretrained deep models outperform GBDTs in Learning-To-Rank under label scarcity. CoRR Charlie Hou, Kiran Koshy Thekumparampil, Michael Shavlovsky, Giulia Fanti, Yesh Dattatreya, Sujay Sanghavi
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
2023	A*	`conf`	Understanding Self-Distillation in the Presence of Label Noise. ICML Rudrajit Das, Sujay Sanghavi
2023	J	`jnl`	Understanding Self-Distillation in the Presence of Label Noise. CoRR Rudrajit Das, Sujay Sanghavi
2023	J	`jnl`	Understanding the Effectiveness of Early Weight Averaging for Training Large Language Models. CoRR Sunny Sanyal, Jean Kaddour, Abhishek Kumar, Sujay Sanghavi
2022	J	`jnl`	An Exponentially Increasing Step-size for Parameter Estimation in Statistical Models. CoRR Nhat Ho, Tongzheng Ren, Sujay Sanghavi, Purnamrita Sarkar, Rachel A. Ward
2022	A*	`conf`	Asymptotically-Optimal Gaussian Bandits with Side Observations. ICML Alexia Atsidakou, Orestis Papadigenopoulos, Constantine Caramanis, Sujay Sanghavi, Sanjay Shakkottai
2022	J	`jnl`	Bayesian Fixed-Budget Best-Arm Identification. CoRR Alexia Atsidakou, Sumeet Katariya, Sujay Sanghavi, Branislav Kveton
2022	J	`jnl`	Beyond EM Algorithm on Over-specified Two-Component Location-Scale Gaussian Mixtures. CoRR Tongzheng Ren, Fuheng Cui, Sujay Sanghavi, Nhat Ho
2022	J	`jnl`	Beyond Uniform Lipschitz Condition in Differentially Private Optimization. CoRR Rudrajit Das, Satyen Kale, Zheng Xu, Tong Zhang, Sujay Sanghavi
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	J	`jnl`	Improving Computational Complexity in Statistical Models with Second-Order Information. CoRR Tongzheng Ren, Jiacheng Zhuo, Sujay Sanghavi, Nhat Ho
2022	J	`jnl`	Latent Variable Representation for Reinforcement Learning. CoRR Tongzheng Ren, Chenjun Xiao, Tianjun Zhang, Na Li, Zhaoran Wang, Sujay Sanghavi, Dale Schuurmans, Bo Dai
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`	Minimax Regret for Cascading Bandits. NeurIPS Daniel Vial, Sujay Sanghavi, Sanjay Shakkottai, R. Srikant
2022	J	`jnl`	Minimax Regret for Cascading Bandits. CoRR Daniel Vial, Sujay Sanghavi, Sanjay Shakkottai, R. Srikant
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`	On the Value of Behavioral Representations for Dense Retrieval. CoRR Nan Jiang, Dhivya Eswaran, Choon Hui Teo, Yexiang Xue, Yesh Dattatreya, Sujay Sanghavi, Vishy Vishwanathan
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	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	J	`jnl`	Sample Efficiency of Data Augmentation Consistency Regularization. CoRR Shuo Yang, Yijun Dong, Rachel A. Ward, Inderjit S. Dhillon, Sujay Sanghavi, Qi Lei
2022	A*	`conf`	Toward Understanding Privileged Features Distillation in Learning-to-Rank. NeurIPS Shuo Yang, Sujay Sanghavi, Holakou Rahmanian, Jan Bakus, S. V. N. Vishwanathan
2022	J	`jnl`	Toward Understanding Privileged Features Distillation in Learning-to-Rank. CoRR Shuo Yang, Sujay Sanghavi, Holakou Rahmanian, Jan Bakus, S. V. N. Vishwanathan
2022	A	`conf`	Towards Statistical and Computational Complexities of Polyak Step Size Gradient Descent. AISTATS Tongzheng Ren, Fuheng Cui, Alexia Atsidakou, Sujay Sanghavi, Nhat Ho
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`	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	J	`jnl`	Linear Bandit Algorithms with Sublinear Time Complexity. CoRR Shuo Yang, Tongzheng Ren, Sanjay Shakkottai, Eric Price, Inderjit S. Dhillon, Sujay Sanghavi
2021	A*	`conf`	Nearly Horizon-Free Offline Reinforcement Learning. NeurIPS Tongzheng Ren, Jialian Li, Bo Dai, Simon S. Du, Sujay Sanghavi
2021	J	`jnl`	Nearly Horizon-Free Offline Reinforcement Learning. CoRR Tongzheng Ren, Jialian Li, Bo Dai, Simon S. Du, Sujay Sanghavi
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	J	`jnl`	Towards Statistical and Computational Complexities of Polyak Step Size Gradient Descent. CoRR Tongzheng Ren, Fuheng Cui, Alexia Atsidakou, Sujay Sanghavi, Nhat Ho
2020	A	`conf`	Choosing the Sample with Lowest Loss makes SGD Robust. AISTATS Vatsal Shah, Xiaoxia Wu, Sujay Sanghavi
2020	J	`jnl`	Choosing the Sample with Lowest Loss makes SGD Robust. CoRR Vatsal Shah, Xiaoxia Wu, Sujay Sanghavi
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`	On Generalization of Adaptive Methods for Over-parameterized Linear Regression. CoRR Vatsal Shah, Soumya Basu, Anastasios Kyrillidis, Sujay Sanghavi
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
2019	A*	`conf`	Blocking Bandits. NeurIPS Soumya Basu, Rajat Sen, Sujay Sanghavi, Sanjay Shakkottai
2019	J	`jnl`	Blocking Bandits. CoRR Soumya Basu, Rajat Sen, Sujay Sanghavi, Sanjay Shakkottai
2019	A*	`conf`	Interaction Hard Thresholding: Consistent Sparse Quadratic Regression in Sub-quadratic Time and Space. NeurIPS Shuo Yang, Yanyao Shen, Sujay Sanghavi
2019	J	`jnl`	Interaction Hard Thresholding: Consistent Sparse Quadratic Regression in Sub-quadratic Time and Space. CoRR Shuo Yang, Yanyao Shen, Sujay Sanghavi
2019	A*	`conf`	Iterative Least Trimmed Squares for Mixed Linear Regression. NeurIPS Yanyao Shen, Sujay Sanghavi
2019	J	`jnl`	Iterative Least Trimmed Squares for Mixed Linear Regression. CoRR Yanyao Shen, Sujay Sanghavi
2019	A*	`conf`	Learning Distributions Generated by One-Layer ReLU Networks. NeurIPS Shanshan Wu, Alexandros G. Dimakis, Sujay Sanghavi
2019	J	`jnl`	Learning Distributions Generated by One-Layer ReLU Networks. CoRR Shanshan Wu, Alexandros G. Dimakis, Sujay Sanghavi
2019	A*	`conf`	Learning a Compressed Sensing Measurement Matrix via Gradient Unrolling. ICML Shanshan Wu, Alex Dimakis, Sujay Sanghavi, Felix X. Yu, Daniel Niels Holtmann-Rice, Dmitry Storcheus, Afshin Rostamizadeh, Sanjiv Kumar
2019	A*	`conf`	Learning with Bad Training Data via Iterative Trimmed Loss Minimization. ICML Yanyao Shen, Sujay Sanghavi
2019	A	`conf`	PruneTrain: fast neural network training by dynamic sparse model reconfiguration. SC Sangkug Lym, Esha Choukse, Siavash Zangeneh, Wei Wen, Sujay Sanghavi, Mattan Erez
2019	A*	`conf`	Sparse Logistic Regression Learns All Discrete Pairwise Graphical Models. NeurIPS Shanshan Wu, Sujay Sanghavi, Alexandros G. Dimakis
2018	J	`jnl`	Finding Low-Rank Solutions via Nonconvex Matrix Factorization, Efficiently and Provably. SIAM J. Imaging Sci. Dohyung Park, Anastasios Kyrillidis, Constantine Caramanis, Sujay Sanghavi
2018	J	`jnl`	Iteratively Learning from the Best. CoRR Yanyao Shen, Sujay Sanghavi
2018	J	`jnl`	Searching for a Single Community in a Graph. CoRR Avik Ray, Sujay Sanghavi, Sanjay Shakkottai
2018	J	`jnl`	Searching for a Single Community in a Graph. ACM Trans. Model. Perform. Evaluation Comput. Syst. Avik Ray, Sujay Sanghavi, Sanjay Shakkottai
2018	J	`jnl`	Sparse Logistic Regression Learns All Discrete Pairwise Graphical Models. CoRR Shanshan Wu, Sujay Sanghavi, Alexandros G. Dimakis
2018	J	`jnl`	The Sparse Recovery Autoencoder. CoRR Shanshan Wu, Alexandros G. Dimakis, Sujay Sanghavi, Felix X. Yu, Daniel Niels Holtmann-Rice, Dmitry Storcheus, Afshin Rostamizadeh, Sanjiv Kumar
2017	A	`conf`	Non-square matrix sensing without spurious local minima via the Burer-Monteiro approach. AISTATS Dohyung Park, Anastasios Kyrillidis, Constantine Caramanis, Sujay Sanghavi
2017	J	`jnl`	Provable quantum state tomography via non-convex methods. CoRR Anastasios Kyrillidis, Amir Kalev, Dohyung Park, Srinadh Bhojanapalli, Constantine Caramanis, Sujay Sanghavi
2017	J	`jnl`	Sparse Quadratic Logistic Regression in Sub-quadratic Time. CoRR Karthikeyan Shanmugam, Murat Kocaoglu, Alexandros G. Dimakis, Sujay Sanghavi
2017	J	`jnl`	The Search Problem in Mixture Models. J. Mach. Learn. Res. Avik Ray, Joe Neeman, Sujay Sanghavi, Sanjay Shakkottai
2016	A*	`conf`	Dropping Convexity for Faster Semi-definite Optimization. COLT Srinadh Bhojanapalli, Anastasios Kyrillidis, Sujay Sanghavi
2016	J	`jnl`	Finding Low-rank Solutions to Matrix Problems, Efficiently and Provably. CoRR Dohyung Park, Anastasios Kyrillidis, Constantine Caramanis, Sujay Sanghavi
2016	—	`conf`	Finding low-rank solutions to smooth convex problems via the Burer-Monteiro approach. Allerton Dohyung Park, Anastasios Kyrillidis, Constantine Caramanis, Sujay Sanghavi
2016	J	`jnl`	Matrix Completion With Column Manipulation: Near-Optimal Sample-Robustness-Rank Tradeoffs. IEEE Trans. Inf. Theory Yudong Chen, Huan Xu, Constantine Caramanis, Sujay Sanghavi
2016	J	`jnl`	Non-square matrix sensing without spurious local minima via the Burer-Monteiro approach. CoRR Dohyung Park, Anastasios Kyrillidis, Constantine Caramanis, Sujay Sanghavi
2016	—	`conf`	Normalized Spectral Map Synchronization. NIPS Yanyao Shen, Qixing Huang, Nati Srebro, Sujay Sanghavi
2016	J	`jnl`	Online Collaborative Filtering on Graphs. Oper. Res. Siddhartha Banerjee, Sujay Sanghavi, Sanjay Shakkottai
2016	J	`jnl`	Online Load Balancing Under Graph Constraints. IEEE/ACM Trans. Netw. Sharayu Moharir, Sujay Sanghavi, Sanjay Shakkottai
2016	J	`jnl`	Provable non-convex projected gradient descent for a class of constrained matrix optimization problems. CoRR Dohyung Park, Anastasios Kyrillidis, Srinadh Bhojanapalli, Constantine Caramanis, Sujay Sanghavi
2016	A*	`conf`	Searching For A Single Community in a Graph. SIGMETRICS Avik Ray, Sujay Sanghavi, Sanjay Shakkottai
2016	—	`conf`	Single Pass PCA of Matrix Products. NIPS Shanshan Wu, Srinadh Bhojanapalli, Sujay Sanghavi, Alexandros G. Dimakis
2016	J	`jnl`	Single Pass PCA of Matrix Products. CoRR Shanshan Wu, Srinadh Bhojanapalli, Sujay Sanghavi, Alexandros G. Dimakis
2016	J	`jnl`	Solving a Mixture of Many Random Linear Equations by Tensor Decomposition and Alternating Minimization. CoRR Xinyang Yi, Constantine Caramanis, Sujay Sanghavi
2016	Misc	`conf`	Structurally-constrained gradient descent for matrix factorization in haplotype assembly problems. ICASSP Changxiao Cai, Sujay Sanghavi, Haris Vikalo
2016	J	`jnl`	Structured Low-Rank Matrix Factorization for Haplotype Assembly. IEEE J. Sel. Top. Signal Process. Changxiao Cai, Sujay Sanghavi, Haris Vikalo
2016	J	`jnl`	The Search Problem in Mixture Models. CoRR Avik Ray, Joe Neeman, Sujay Sanghavi, Sanjay Shakkottai
2016	J	`jnl`	Trading-off variance and complexity in stochastic gradient descent. CoRR Vatsal Shah, Megasthenis Asteris, Anastasios Kyrillidis, Sujay Sanghavi
2015	J	`jnl`	A New Sampling Technique for Tensors. CoRR Srinadh Bhojanapalli, Sujay Sanghavi
2015	J	`jnl`	Completing any low-rank matrix, provably. J. Mach. Learn. Res. Yudong Chen, Srinadh Bhojanapalli, Sujay Sanghavi, Rachel A. Ward
2015	—	`conf`	Convergence Rates of Active Learning for Maximum Likelihood Estimation. NIPS Kamalika Chaudhuri, Sham M. Kakade, Praneeth Netrapalli, Sujay Sanghavi
2015	J	`jnl`	Convergence Rates of Active Learning for Maximum Likelihood Estimation. CoRR Kamalika Chaudhuri, Sham M. Kakade, Praneeth Netrapalli, Sujay Sanghavi
2015	J	`jnl`	Dropping Convexity for Faster Semi-definite Optimization. CoRR Srinadh Bhojanapalli, Anastasios Kyrillidis, Sujay Sanghavi
2015	J	`jnl`	Improved Greedy Algorithms for Learning Graphical Models. IEEE Trans. Inf. Theory Avik Ray, Sujay Sanghavi, Sanjay Shakkottai
2015	J	`jnl`	Phase Retrieval Using Alternating Minimization. IEEE Trans. Signal Process. Praneeth Netrapalli, Prateek Jain, Sujay Sanghavi
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	J	`jnl`	Serving content with unknown demand: the high-dimensional regime. Queueing Syst. Theory Appl. Sharayu Moharir, Javad Ghaderi, Sujay Sanghavi, Sanjay Shakkottai
2015	A*	`conf`	Tighter Low-rank Approximation via Sampling the Leveraged Element. SODA Srinadh Bhojanapalli, Prateek Jain, Sujay Sanghavi
2014	A*	`ed.`	ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems, SIGMETRICS 2014, Austin, TX, USA, June 16-20, 2014 SIGMETRICS Sujay Sanghavi, Sanjay Shakkottai, Marc Lelarge, Bianca Schroeder
2014	A*	`conf`	Alternating Minimization for Mixed Linear Regression. ICML Xinyang Yi, Constantine Caramanis, Sujay Sanghavi
2014	J	`jnl`	Clustering partially observed graphs via convex optimization. J. Mach. Learn. Res. Yudong Chen, Ali Jalali, Sujay Sanghavi, Huan Xu
2014	A*	`conf`	Coherent Matrix Completion. ICML Yudong Chen, Srinadh Bhojanapalli, Sujay Sanghavi, Rachel A. Ward
2014	—	`conf`	Greedy Subspace Clustering. NIPS Dohyung Park, Constantine Caramanis, Sujay Sanghavi
2014	J	`jnl`	Greedy Subspace Clustering. CoRR Dohyung Park, Constantine Caramanis, Sujay Sanghavi
2014	J	`jnl`	Improved Graph Clustering. IEEE Trans. Inf. Theory Yudong Chen, Sujay Sanghavi, Huan Xu
2014	B	`conf`	Learning structure of power-law Markov networks. ISIT Abhik Kumar Das, Praneeth Netrapalli, Sujay Sanghavi, Sriram Vishwanath
2014	—	`conf`	Non-convex Robust PCA. NIPS Praneeth Netrapalli, U. N. Niranjan, Sujay Sanghavi, Animashree Anandkumar, Prateek Jain
2014	J	`jnl`	Non-convex Robust PCA. CoRR Praneeth Netrapalli, U. N. Niranjan, Sujay Sanghavi, Animashree Anandkumar, Prateek Jain
2014	J	`jnl`	Online Collaborative-Filtering on Graphs. CoRR Siddhartha Banerjee, Sujay Sanghavi, Sanjay Shakkottai
2014	—	`conf`	Overlap graph clustering via successive removal. Allerton Avik Ray, Javad Ghaderi, Sujay Sanghavi, Sanjay Shakkottai
2014	J	`jnl`	Serving Content with Unknown Demand: the High-Dimensional Regime. CoRR Sharayu Moharir, Javad Ghaderi, Sujay Sanghavi, Sanjay Shakkottai
2014	A*	`conf`	Serving content with unknown demand: the high-dimensional regime. SIGMETRICS Sharayu Moharir, Javad Ghaderi, Sujay Sanghavi, Sanjay Shakkottai
2014	J	`jnl`	Tighter Low-rank Approximation via Sampling the Leveraged Element. CoRR Srinadh Bhojanapalli, Prateek Jain, Sujay Sanghavi
2014	A*	`conf`	Topic modeling from network spread. SIGMETRICS Avik Ray, Sujay Sanghavi, Sanjay Shakkottai
2013	J	`jnl`	A Dirty Model for Multiple Sparse Regression. IEEE Trans. Inf. Theory Ali Jalali, Pradeep Ravikumar, Sujay Sanghavi
2013	J	`jnl`	Coherent Matrix Completion. CoRR Srinadh Bhojanapalli, Yudong Chen, Sujay Sanghavi, Rachel A. Ward
2013	—	`conf`	Learning the causal graph of Markov time series. Allerton Avhishek Chatterjee, Ankit Singh Rawat, Sriram Vishwanath, Sujay Sanghavi
2013	J	`jnl`	Low-Rank Matrix Recovery From Errors and Erasures. IEEE Trans. Inf. Theory Yudong Chen, Ali Jalali, Sujay Sanghavi, Constantine Caramanis
2013	A*	`conf`	Low-rank matrix completion using alternating minimization. STOC Prateek Jain, Praneeth Netrapalli, Sujay Sanghavi
2013	A*	`conf`	Online load balancing under graph constraints. SIGMETRICS Sharayu Moharir, Sujay Sanghavi, Sanjay Shakkottai
2013	—	`conf`	Phase Retrieval using Alternating Minimization. NIPS Praneeth Netrapalli, Prateek Jain, Sujay Sanghavi
2013	J	`jnl`	Phase Retrieval using Alternating Minimization. CoRR Praneeth Netrapalli, Prateek Jain, Sujay Sanghavi
2012	J	`jnl`	A New Greedy Algorithm for Multiple Sparse Regression CoRR Ali Jalali, Sujay Sanghavi
2012	—	`conf`	Clustering Sparse Graphs. NIPS Yudong Chen, Sujay Sanghavi, Huan Xu
2012	J	`jnl`	Finding the Graph of Epidemic Cascades CoRR Praneeth Netrapalli, Sujay Sanghavi
2012	—	`conf`	Greedy dirty models: A new algorithm for multiple sparse regression. SSP Ali Jalali, Sujay Sanghavi
2012	—	`conf`	Greedy learning of graphical models with small girth. Allerton Conference Avik Ray, Sujay Sanghavi, Sanjay Shakkottai
2012	B	`conf`	Learning Markov graphs up to edit distance. ISIT Abhik Kumar Das, Praneeth Netrapalli, Sujay Sanghavi, Sriram Vishwanath
2012	A*	`conf`	Learning the Dependence Graph of Time Series with Latent Factors. ICML Ali Jalali, Sujay Sanghavi
2012	A*	`conf`	Learning the graph of epidemic cascades. SIGMETRICS Praneeth Netrapalli, Sujay Sanghavi
2012	J	`jnl`	Low-rank Matrix Completion using Alternating Minimization CoRR Prateek Jain, Praneeth Netrapalli, Sujay Sanghavi
2012	J	`jnl`	On the Effect of Channel Fading on Greedy Scheduling CoRR Aneesh Reddy, Sujay Sanghavi, Sanjay Shakkottai
2012	A*	`conf`	On the effect of channel fading on greedy scheduling. INFOCOM Aneesh Reddy, Sujay Sanghavi, Sanjay Shakkottai
2012	—	`conf`	Online load balancing and correlated randomness. Allerton Conference Sharayu Moharir, Sujay Sanghavi
2012	J	`jnl`	Robust PCA via Outlier Pursuit. IEEE Trans. Inf. Theory Huan Xu, Constantine Caramanis, Sujay Sanghavi
2011	J	`jnl`	A Dirty Model for Multiple Sparse Regression CoRR Ali Jalali, Pradeep Ravikumar, Sujay Sanghavi
2011	J	`jnl`	Belief Propagation and LP Relaxation for Weighted Matching in General Graphs. IEEE Trans. Inf. Theory Sujay Sanghavi, Dmitry M. Malioutov, Alan S. Willsky
2011	J	`jnl`	Clustering Partially Observed Graphs via Convex Optimization CoRR Ali Jalali, Yudong Chen, Sujay Sanghavi, Huan Xu
2011	A*	`conf`	Clustering Partially Observed Graphs via Convex Optimization. ICML Ali Jalali, Yudong Chen, Sujay Sanghavi, Huan Xu
2011	J	`jnl`	Learning with Latent Factors in Time Series CoRR Ali Jalali, Sujay Sanghavi
2011	J	`jnl`	Low-rank Matrix Recovery from Errors and Erasures CoRR Yudong Chen, Ali Jalali, Sujay Sanghavi, Constantine Caramanis
2011	B	`conf`	Low-rank matrix recovery from errors and erasures. ISIT Yudong Chen, Ali Jalali, Sujay Sanghavi, Constantine Caramanis
2011	A	`conf`	On Learning Discrete Graphical Models using Group-Sparse Regularization. AISTATS Ali Jalali, Pradeep Ravikumar, Vishvas Vasuki, Sujay Sanghavi
2011	J	`jnl`	Rank-Sparsity Incoherence for Matrix Decomposition. SIAM J. Optim. Venkat Chandrasekaran, Sujay Sanghavi, Pablo A. Parrilo, Alan S. Willsky
2011	A*	`conf`	Robust Matrix Completion and Corrupted Columns. ICML Yudong Chen, Huan Xu, Constantine Caramanis, Sujay Sanghavi
2011	J	`jnl`	Robust Matrix Completion with Corrupted Columns CoRR Yudong Chen, Huan Xu, Constantine Caramanis, Sujay Sanghavi
2010	—	`conf`	A Dirty Model for Multi-task Learning. NIPS Ali Jalali, Pradeep Ravikumar, Sujay Sanghavi, Chao Ruan
2010	—	`conf`	A general framework for high-dimensional estimation in the presence of incoherence. Allerton Yuxin Chen, Sujay Sanghavi
2010	—	`conf`	Greedy learning of Markov network structure. Allerton Praneeth Netrapalli, Siddhartha Banerjee, Sujay Sanghavi, Sanjay Shakkottai
2010	J	`jnl`	Learning graphical models for hypothesis testing and classification. IEEE Trans. Signal Process. Vincent Y. F. Tan, Sujay Sanghavi, John W. Fisher III, Alan S. Willsky
2010	J	`jnl`	Robust PCA via Outlier Pursuit CoRR Huan Xu, Constantine Caramanis, Sujay Sanghavi
2010	—	`conf`	Robust PCA via Outlier Pursuit. NIPS Huan Xu, Constantine Caramanis, Sujay Sanghavi
2010	J	`jnl`	Sequential Compressed Sensing CoRR Dmitry M. Malioutov, Sujay Sanghavi, Alan S. Willsky
2010	J	`jnl`	Sequential Compressed Sensing. IEEE J. Sel. Top. Signal Process. Dmitry M. Malioutov, Sujay Sanghavi, Alan S. Willsky
2009	Misc	`conf`	Conferencing on trees. CISS Ali Jalali, David James Love, Sujay Sanghavi, Bertrand M. Hochwald
2009	J	`jnl`	Distributed link scheduling with constant overhead. IEEE/ACM Trans. Netw. Loc Bui, Sujay Sanghavi, R. Srikant
2009	—	`conf`	Is it enough to drain the heaviest bottlenecks? Allerton Gagan Raj Gupta, Sujay Sanghavi, Ness B. Shroff
2009	J	`jnl`	Message passing for maximum weight independent set. IEEE Trans. Inf. Theory Sujay Sanghavi, Devavrat Shah, Alan S. Willsky
2009	J	`jnl`	Node Weighted Scheduling CoRR Gagan Raj Gupta, Sujay Sanghavi, Ness B. Shroff
2009	—	`conf`	Node weighted scheduling. SIGMETRICS/Performance Gagan Raj Gupta, Sujay Sanghavi, Ness B. Shroff
2009	B	`conf`	Some fundamental coding theoretic limits of unequal error protection. ISIT Shashi Borade, Sujay Sanghavi
2009	—	`conf`	Sparse and low-rank matrix decompositions. Allerton Venkat Chandrasekaran, Sujay Sanghavi, Pablo A. Parrilo, Alan S. Willsky
2009	J	`jnl`	Workload optimality in switches without arrivals. SIGMETRICS Perform. Evaluation Rev. Gagan Raj Gupta, Sujay Sanghavi, Ness B. Shroff
2008	J	`jnl`	A New Mechanism for the Free-Rider Problem. IEEE Trans. Autom. Control. Sujay Sanghavi, Bruce E. Hajek
2008	Misc	`conf`	Compressed sensing with sequential observations. ICASSP Dmitry M. Malioutov, Sujay Sanghavi, Alan S. Willsky
2008	J	`jnl`	Message-passing for Maximum Weight Independent Set CoRR Sujay Sanghavi, Devavrat Shah, Alan S. Willsky
2008	—	`conf`	Networking sensors using belief propagation. Allerton Sujay Sanghavi, Dmitry Malioutov, Alan S. Willsky
2007	A*	`conf`	Distributed link scheduling with constant overhead. SIGMETRICS Sujay Sanghavi, Loc Bui, R. Srikant
2007	J	`jnl`	Equivalence of LP Relaxation and Max-Product for Weighted Matching in General Graphs CoRR Sujay Sanghavi
2007	J	`jnl`	Gossiping With Multiple Messages. IEEE Trans. Inf. Theory Sujay Sanghavi, Bruce E. Hajek, Laurent Massoulié
2007	A*	`conf`	Gossiping with Multiple Messages. INFOCOM Sujay Sanghavi, Bruce E. Hajek, Laurent Massoulié
2007	—	`conf`	Linear programming analysis of loopy belief propagation for weighted matching. NIPS Sujay Sanghavi, Dmitry M. Malioutov, Alan S. Willsky
2007	—	`conf`	Message Passing for Max-weight Independent Set. NIPS Sujay Sanghavi, Devavrat Shah, Alan S. Willsky
2006	J	`jnl`	Adaptive induced fluctuations for multiuser diversity. IEEE Trans. Wirel. Commun. Sujay Sanghavi, Bruce E. Hajek
2006	—	`—`	Decentralized Network Algorithms Sujay Sanghavi
2006	J	`jnl`	Distributed Link Scheduling with Constant Overhead CoRR Sujay Sanghavi, Loc Bui, R. Srikant
2006	J	`jnl`	Gossiping with Multiple Messages CoRR Sujay Sanghavi, Bruce E. Hajek, Laurent Massoulié
2006	J	`jnl`	Intermediate Performance of Rateless Codes CoRR Sujay Sanghavi
2005	—	`conf`	A new mechanism for the free-rider problem. P2PECON@SIGCOMM Sujay Sanghavi, Bruce E. Hajek
2004	—	`conf`	Optimal allocation of a divisible good to strategic buyers. CDC Sujay Sanghavi, Bruce E. Hajek