Sujay Sanghavi

According to our database, Sujay Sanghavi authored at least 134 papers between 2004 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

RARe: Retrieval Augmented Retrieval with In-Context Examples.

Atula Tejaswi, Yoonsang Lee, Sujay Sanghavi, Eunsol Choi

CoRR, 2024

Geometric Median (GM) Matching for Robust Data Pruning.

Anish Acharya, Inderjit S. Dhillon, Sujay Sanghavi

CoRR, 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 Yitzhak Gadre, Hritik Bansal, Etash Kumar 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 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

CoRR, 2024

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

CoRR, 2024

Adaptive and Optimal Second-order Optimistic Methods for Minimax Optimization.

Ruichen Jiang, Ali Kavis, Qiujiang Jin, Sujay Sanghavi, Aryan Mokhtari

CoRR, 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

CoRR, 2024

Pre-training Small Base LMs with Fewer Tokens.

Sunny Sanyal, Sujay Sanghavi, Alexandros G. Dimakis

CoRR, 2024

In-Context Learning with Transformers: Softmax Attention Adapts to Function Lipschitzness.

Liam Collins, Advait Parulekar, Aryan Mokhtari, Sujay Sanghavi, Sanjay Shakkottai

CoRR, 2024

Towards Quantifying the Preconditioning Effect of Adam.

Rudrajit Das, Naman Agarwal, Sujay Sanghavi, Inderjit S. Dhillon

CoRR, 2024

Contrastive Approach to Prior Free Positive Unlabeled Learning.

Anish Acharya, Sujay Sanghavi

CoRR, 2024

Time Weaver: A Conditional Time Series Generation Model.

Sai Shankar Narasimhan, Shubhankar Agarwal, Oguzhan Akcin, Sujay Sanghavi, Sandeep P. Chinchali

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Understanding the Training Speedup from Sampling with Approximate Losses.

Rudrajit Das, Xi Chen, Bertram Ieong, Parikshit Bansal, Sujay Sanghavi

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Improving Computational Complexity in Statistical Models with Local Curvature Information.

Pedram Akbarian, Tongzheng Ren, Jiacheng Zhuo, Sujay Sanghavi, Nhat Ho

Proceedings of the Forty-first International Conference on Machine Learning, 2024

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

CoRR, 2023

Understanding the Effectiveness of Early Weight Averaging for Training Large Language Models.

Sunny Sanyal, Jean Kaddour, Abhishek Kumar, Sujay Sanghavi

CoRR, 2023

Logarithmic Bayes Regret Bounds.

Alexia Atsidakou, Branislav Kveton, Sumeet Katariya, Constantine Caramanis, Sujay Sanghavi

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Understanding Self-Distillation in the Presence of Label Noise.

Rudrajit Das, Sujay Sanghavi

Proceedings of the International Conference on Machine Learning, 2023

Beyond Uniform Lipschitz Condition in Differentially Private Optimization.

Rudrajit Das, Satyen Kale, Zheng Xu, Tong Zhang, Sujay Sanghavi

Proceedings of the International Conference on Machine Learning, 2023

Latent Variable Representation for Reinforcement Learning.

Tongzheng Ren, Chenjun Xiao, Tianjun Zhang, Na Li, Zhaoran Wang, Sujay Sanghavi, Dale Schuurmans, Bo Dai

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Sample Efficiency of Data Augmentation Consistency Regularization.

Shuo Yang, Yijun Dong, Rachel A. Ward, Inderjit S. Dhillon, Sujay Sanghavi, Qi Lei

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

On the Benefits of Multiple Gossip Steps in Communication-Constrained Decentralized Federated Learning.

Abolfazl Hashemi, Anish Acharya, Rudrajit Das, Haris Vikalo, Sujay Sanghavi, Inderjit S. Dhillon

IEEE Trans. Parallel Distributed Syst., 2022

Bayesian Fixed-Budget Best-Arm Identification.

Alexia Atsidakou, Sumeet Katariya, Sujay Sanghavi, Branislav Kveton

CoRR, 2022

On the Value of Behavioral Representations for Dense Retrieval.

Nan Jiang, Dhivya Eswaran, Choon Hui Teo, Yexiang Xue, Yesh Dattatreya, Sujay Sanghavi, Vishy Vishwanathan

CoRR, 2022

Positive Unlabeled Contrastive Learning.

Anish Acharya, Sujay Sanghavi, Li Jing, Bhargav Bhushanam, Dhruv Choudhary, Michael G. Rabbat, Inderjit S. Dhillon

CoRR, 2022

Beyond EM Algorithm on Over-specified Two-Component Location-Scale Gaussian Mixtures.

Tongzheng Ren, Fuheng Cui, Sujay Sanghavi, Nhat Ho

CoRR, 2022

An Exponentially Increasing Step-size for Parameter Estimation in Statistical Models.

Nhat Ho, Tongzheng Ren, Sujay Sanghavi, Purnamrita Sarkar, Rachel A. Ward

CoRR, 2022

Improving Computational Complexity in Statistical Models with Second-Order Information.

Tongzheng Ren, Jiacheng Zhuo, Sujay Sanghavi, Nhat Ho

CoRR, 2022

Faster non-convex federated learning via global and local momentum.

Rudrajit Das, Anish Acharya, Abolfazl Hashemi, Sujay Sanghavi, Inderjit S. Dhillon, Ufuk Topcu

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Toward Understanding Privileged Features Distillation in Learning-to-Rank.

Shuo Yang, Sujay Sanghavi, Holakou Rahmanian, Jan Bakus, S. V. N. Vishwanathan

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Minimax Regret for Cascading Bandits.

Daniel Vial, Sujay Sanghavi, Sanjay Shakkottai, R. Srikant

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Linear Bandit Algorithms with Sublinear Time Complexity.

Shuo Yang, Tongzheng Ren, Sanjay Shakkottai, Eric Price, Inderjit S. Dhillon, Sujay Sanghavi

Proceedings of the International Conference on Machine Learning, 2022

Asymptotically-Optimal Gaussian Bandits with Side Observations.

Alexia Atsidakou, Orestis Papadigenopoulos, Constantine Caramanis, Sujay Sanghavi, Sanjay Shakkottai

Proceedings of the International Conference on Machine Learning, 2022

Towards Statistical and Computational Complexities of Polyak Step Size Gradient Descent.

Tongzheng Ren, Fuheng Cui, Alexia Atsidakou, Sujay Sanghavi, Nhat Ho

Proceedings of the International Conference on Artificial Intelligence and Statistics, 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

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

DP-NormFedAvg: Normalizing Client Updates for Privacy-Preserving Federated Learning.

Rudrajit Das, Abolfazl Hashemi, Sujay Sanghavi, Inderjit S. Dhillon

CoRR, 2021

Combinatorial Bandits without Total Order for Arms.

Shuo Yang, Tongzheng Ren, Inderjit S. Dhillon, Sujay Sanghavi

CoRR, 2021

Nearly Horizon-Free Offline Reinforcement Learning.

Tongzheng Ren, Jialian Li, Bo Dai, Simon S. Du, Sujay Sanghavi

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Enabling Efficiency-Precision Trade-offs for Label Trees in Extreme Classification.

Tavor Z. Baharav, Daniel L. Jiang, Kedarnath Kolluri, Sujay Sanghavi, Inderjit S. Dhillon

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020

Improved Convergence Rates for Non-Convex Federated Learning with Compression.

Rudrajit Das, Abolfazl Hashemi, Sujay Sanghavi, Inderjit S. Dhillon

CoRR, 2020

On Generalization of Adaptive Methods for Over-parameterized Linear Regression.

Vatsal Shah, Soumya Basu, Anastasios Kyrillidis, Sujay Sanghavi

CoRR, 2020

On the Benefits of Multiple Gossip Steps in Communication-Constrained Decentralized Optimization.

Abolfazl Hashemi, Anish Acharya, Rudrajit Das, Haris Vikalo, Sujay Sanghavi, Inderjit S. Dhillon

CoRR, 2020

Extreme Multi-label Classification from Aggregated Labels.

Yanyao Shen, Hsiang-Fu Yu, Sujay Sanghavi, Inderjit S. Dhillon

Proceedings of the 37th International Conference on Machine Learning, 2020

Choosing the Sample with Lowest Loss makes SGD Robust.

Vatsal Shah, Xiaoxia Wu, Sujay Sanghavi

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

PruneTrain: fast neural network training by dynamic sparse model reconfiguration.

Sangkug Lym, Esha Choukse, Siavash Zangeneh, Wei Wen, Sujay Sanghavi, Mattan Erez

Proceedings of the International Conference for High Performance Computing, 2019

Interaction Hard Thresholding: Consistent Sparse Quadratic Regression in Sub-quadratic Time and Space.

Shuo Yang, Yanyao Shen, Sujay Sanghavi

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Sparse Logistic Regression Learns All Discrete Pairwise Graphical Models.

Shanshan Wu, Sujay Sanghavi, Alexandros G. Dimakis

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Learning Distributions Generated by One-Layer ReLU Networks.

Shanshan Wu, Alexandros G. Dimakis, Sujay Sanghavi

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Iterative Least Trimmed Squares for Mixed Linear Regression.

Yanyao Shen, Sujay Sanghavi

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Blocking Bandits.

Soumya Basu, Rajat Sen, Sujay Sanghavi, Sanjay Shakkottai

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Learning a Compressed Sensing Measurement Matrix via Gradient Unrolling.

Shanshan Wu, Alex Dimakis, Sujay Sanghavi, Felix X. Yu, Daniel Niels Holtmann-Rice, Dmitry Storcheus, Afshin Rostamizadeh, Sanjiv Kumar

Proceedings of the 36th International Conference on Machine Learning, 2019

Learning with Bad Training Data via Iterative Trimmed Loss Minimization.

Yanyao Shen, Sujay Sanghavi

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Searching for a Single Community in a Graph.

Avik Ray, Sujay Sanghavi, Sanjay Shakkottai

ACM Trans. Model. Perform. Evaluation Comput. Syst., 2018

Finding Low-Rank Solutions via Nonconvex Matrix Factorization, Efficiently and Provably.

Dohyung Park, Anastasios Kyrillidis, Constantine Caramanis, Sujay Sanghavi

SIAM J. Imaging Sci., 2018

Iteratively Learning from the Best.

Yanyao Shen, Sujay Sanghavi

CoRR, 2018

The Sparse Recovery Autoencoder.

Shanshan Wu, Alexandros G. Dimakis, Sujay Sanghavi, Felix X. Yu, Daniel Niels Holtmann-Rice, Dmitry Storcheus, Afshin Rostamizadeh, Sanjiv Kumar

CoRR, 2018

2017

The Search Problem in Mixture Models.

Avik Ray, Joe Neeman, Sujay Sanghavi, Sanjay Shakkottai

J. Mach. Learn. Res., 2017

Provable quantum state tomography via non-convex methods.

Anastasios Kyrillidis, Amir Kalev, Dohyung Park, Srinadh Bhojanapalli, Constantine Caramanis, Sujay Sanghavi

CoRR, 2017

Sparse Quadratic Logistic Regression in Sub-quadratic Time.

Karthikeyan Shanmugam, Murat Kocaoglu, Alexandros G. Dimakis, Sujay Sanghavi

CoRR, 2017

Non-square matrix sensing without spurious local minima via the Burer-Monteiro approach.

Dohyung Park, Anastasios Kyrillidis, Constantine Caramanis, Sujay Sanghavi

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016

Online Load Balancing Under Graph Constraints.

Sharayu Moharir, Sujay Sanghavi, Sanjay Shakkottai

IEEE/ACM Trans. Netw., 2016

Matrix Completion With Column Manipulation: Near-Optimal Sample-Robustness-Rank Tradeoffs.

Yudong Chen, Huan Xu, Constantine Caramanis, Sujay Sanghavi

IEEE Trans. Inf. Theory, 2016

Structured Low-Rank Matrix Factorization for Haplotype Assembly.

Changxiao Cai, Sujay Sanghavi, Haris Vikalo

IEEE J. Sel. Top. Signal Process., 2016

Online Collaborative Filtering on Graphs.

Siddhartha Banerjee, Sujay Sanghavi, Sanjay Shakkottai

Oper. Res., 2016

Solving a Mixture of Many Random Linear Equations by Tensor Decomposition and Alternating Minimization.

Xinyang Yi, Constantine Caramanis, Sujay Sanghavi

CoRR, 2016

Trading-off variance and complexity in stochastic gradient descent.

Vatsal Shah, Megasthenis Asteris, Anastasios Kyrillidis, Sujay Sanghavi

CoRR, 2016

Finding Low-rank Solutions to Matrix Problems, Efficiently and Provably.

Dohyung Park, Anastasios Kyrillidis, Constantine Caramanis, Sujay Sanghavi

CoRR, 2016

Provable non-convex projected gradient descent for a class of constrained matrix optimization problems.

Dohyung Park, Anastasios Kyrillidis, Srinadh Bhojanapalli, Constantine Caramanis, Sujay Sanghavi

CoRR, 2016

Single Pass PCA of Matrix Products.

Shanshan Wu, Srinadh Bhojanapalli, Sujay Sanghavi, Alexandros G. Dimakis

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Normalized Spectral Map Synchronization.

Yanyao Shen, Qixing Huang, Nati Srebro, Sujay Sanghavi

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Structurally-constrained gradient descent for matrix factorization in haplotype assembly problems.

Changxiao Cai, Sujay Sanghavi, Haris Vikalo

Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

Dropping Convexity for Faster Semi-definite Optimization.

Srinadh Bhojanapalli, Anastasios Kyrillidis, Sujay Sanghavi

Proceedings of the 29th Conference on Learning Theory, 2016

Finding low-rank solutions to smooth convex problems via the Burer-Monteiro approach.

Dohyung Park, Anastasios Kyrillidis, Constantine Caramanis, Sujay Sanghavi

Proceedings of the 54th Annual Allerton Conference on Communication, 2016

2015

Phase Retrieval Using Alternating Minimization.

Praneeth Netrapalli, Prateek Jain, Sujay Sanghavi

IEEE Trans. Signal Process., 2015

Improved Greedy Algorithms for Learning Graphical Models.

Avik Ray, Sujay Sanghavi, Sanjay Shakkottai

IEEE Trans. Inf. Theory, 2015

Serving content with unknown demand: the high-dimensional regime.

Sharayu Moharir, Javad Ghaderi, Sujay Sanghavi, Sanjay Shakkottai

Queueing Syst. Theory Appl., 2015

Completing any low-rank matrix, provably.

Yudong Chen, Srinadh Bhojanapalli, Sujay Sanghavi, Rachel A. Ward

J. Mach. Learn. Res., 2015

A New Sampling Technique for Tensors.

Srinadh Bhojanapalli, Sujay Sanghavi

CoRR, 2015

Tighter Low-rank Approximation via Sampling the Leveraged Element.

Srinadh Bhojanapalli, Prateek Jain, Sujay Sanghavi

Proceedings of the Twenty-Sixth Annual ACM-SIAM Symposium on Discrete Algorithms, 2015

Convergence Rates of Active Learning for Maximum Likelihood Estimation.

Kamalika Chaudhuri, Sham M. Kakade, Praneeth Netrapalli, Sujay Sanghavi

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Preference Completion: Large-scale Collaborative Ranking from Pairwise Comparisons.

Dohyung Park, Joe Neeman, Jin Zhang, Sujay Sanghavi, Inderjit S. Dhillon

Proceedings of the 32nd International Conference on Machine Learning, 2015

2014

Improved Graph Clustering.

Yudong Chen, Sujay Sanghavi, Huan Xu

IEEE Trans. Inf. Theory, 2014

Clustering partially observed graphs via convex optimization.

Yudong Chen, Ali Jalali, Sujay Sanghavi, Huan Xu

J. Mach. Learn. Res., 2014

Topic modeling from network spread.

Avik Ray, Sujay Sanghavi, Sanjay Shakkottai

Proceedings of the ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems, 2014

Greedy Subspace Clustering.

Dohyung Park, Constantine Caramanis, Sujay Sanghavi

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Non-convex Robust PCA.

Praneeth Netrapalli, U. N. Niranjan, Sujay Sanghavi, Animashree Anandkumar, Prateek Jain

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Learning structure of power-law Markov networks.

Abhik Kumar Das, Praneeth Netrapalli, Sujay Sanghavi, Sriram Vishwanath

Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014

Alternating Minimization for Mixed Linear Regression.

Xinyang Yi, Constantine Caramanis, Sujay Sanghavi

Proceedings of the 31th International Conference on Machine Learning, 2014

Coherent Matrix Completion.

Yudong Chen, Srinadh Bhojanapalli, Sujay Sanghavi, Rachel A. Ward

Proceedings of the 31th International Conference on Machine Learning, 2014

Overlap graph clustering via successive removal.

Avik Ray, Javad Ghaderi, Sujay Sanghavi, Sanjay Shakkottai

Proceedings of the 52nd Annual Allerton Conference on Communication, 2014

2013

A Dirty Model for Multiple Sparse Regression.

Ali Jalali, Pradeep Ravikumar, Sujay Sanghavi

IEEE Trans. Inf. Theory, 2013

Low-Rank Matrix Recovery From Errors and Erasures.

Yudong Chen, Ali Jalali, Sujay Sanghavi, Constantine Caramanis

IEEE Trans. Inf. Theory, 2013

Low-rank matrix completion using alternating minimization.

Prateek Jain, Praneeth Netrapalli, Sujay Sanghavi

Proceedings of the Symposium on Theory of Computing Conference, 2013

Learning the causal graph of Markov time series.

Avhishek Chatterjee, Ankit Singh Rawat, Sriram Vishwanath, Sujay Sanghavi

Proceedings of the 51st Annual Allerton Conference on Communication, 2013

2012

Robust PCA via Outlier Pursuit.

Huan Xu, Constantine Caramanis, Sujay Sanghavi

IEEE Trans. Inf. Theory, 2012

A New Greedy Algorithm for Multiple Sparse Regression

Ali Jalali, Sujay Sanghavi

CoRR, 2012

Finding the Graph of Epidemic Cascades

Praneeth Netrapalli, Sujay Sanghavi

CoRR, 2012

Greedy dirty models: A new algorithm for multiple sparse regression.

Ali Jalali, Sujay Sanghavi

Proceedings of the IEEE Statistical Signal Processing Workshop, 2012

Learning the graph of epidemic cascades.

Praneeth Netrapalli, Sujay Sanghavi

Proceedings of the ACM SIGMETRICS/PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems, 2012

Clustering Sparse Graphs.

Yudong Chen, Sujay Sanghavi, Huan Xu

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Learning Markov graphs up to edit distance.

Abhik Kumar Das, Praneeth Netrapalli, Sujay Sanghavi, Sriram Vishwanath

Proceedings of the 2012 IEEE International Symposium on Information Theory, 2012

On the effect of channel fading on greedy scheduling.

Aneesh Reddy, Sujay Sanghavi, Sanjay Shakkottai

Proceedings of the IEEE INFOCOM 2012, Orlando, FL, USA, March 25-30, 2012, 2012

Learning the Dependence Graph of Time Series with Latent Factors.

Ali Jalali, Sujay Sanghavi

Proceedings of the 29th International Conference on Machine Learning, 2012

Greedy learning of graphical models with small girth.

Avik Ray, Sujay Sanghavi, Sanjay Shakkottai

Proceedings of the 50th Annual Allerton Conference on Communication, 2012

Online load balancing and correlated randomness.

Sharayu Moharir, Sujay Sanghavi

Proceedings of the 50th Annual Allerton Conference on Communication, 2012

2011

Belief Propagation and LP Relaxation for Weighted Matching in General Graphs.

Sujay Sanghavi, Dmitry M. Malioutov, Alan S. Willsky

IEEE Trans. Inf. Theory, 2011

Rank-Sparsity Incoherence for Matrix Decomposition.

Venkat Chandrasekaran, Sujay Sanghavi, Pablo A. Parrilo, Alan S. Willsky

SIAM J. Optim., 2011

On Learning Discrete Graphical Models using Group-Sparse Regularization.

Ali Jalali, Pradeep Ravikumar, Vishvas Vasuki, Sujay Sanghavi

Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

Learning with Latent Factors in Time Series

Ali Jalali, Sujay Sanghavi

CoRR, 2011

Robust Matrix Completion with Corrupted Columns

Yudong Chen, Huan Xu, Constantine Caramanis, Sujay Sanghavi

CoRR, 2011

Robust Matrix Completion and Corrupted Columns.

Yudong Chen, Huan Xu, Constantine Caramanis, Sujay Sanghavi

Proceedings of the 28th International Conference on Machine Learning, 2011

2010

Learning graphical models for hypothesis testing and classification.

Vincent Y. F. Tan, Sujay Sanghavi, John W. Fisher III, Alan S. Willsky

IEEE Trans. Signal Process., 2010

Sequential Compressed Sensing.

Dmitry M. Malioutov, Sujay Sanghavi, Alan S. Willsky

IEEE J. Sel. Top. Signal Process., 2010

A Dirty Model for Multi-task Learning.

Ali Jalali, Pradeep Ravikumar, Sujay Sanghavi, Chao Ruan

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Greedy learning of Markov network structure.

Praneeth Netrapalli, Siddhartha Banerjee, Sujay Sanghavi, Sanjay Shakkottai

Proceedings of the 48th Annual Allerton Conference on Communication, 2010

A general framework for high-dimensional estimation in the presence of incoherence.

Yuxin Chen, Sujay Sanghavi

Proceedings of the 48th Annual Allerton Conference on Communication, 2010

2009

Distributed link scheduling with constant overhead.

Loc Bui, Sujay Sanghavi, R. Srikant

IEEE/ACM Trans. Netw., 2009

Message passing for maximum weight independent set.

Sujay Sanghavi, Devavrat Shah, Alan S. Willsky

IEEE Trans. Inf. Theory, 2009

Workload optimality in switches without arrivals.

Gagan Raj Gupta, Sujay Sanghavi, Ness B. Shroff

SIGMETRICS Perform. Evaluation Rev., 2009

Node weighted scheduling.

Gagan Raj Gupta, Sujay Sanghavi, Ness B. Shroff

Proceedings of the Eleventh International Joint Conference on Measurement and Modeling of Computer Systems, 2009

Some fundamental coding theoretic limits of unequal error protection.

Shashi Borade, Sujay Sanghavi

Proceedings of the IEEE International Symposium on Information Theory, 2009

Conferencing on trees.

Ali Jalali, David James Love, Sujay Sanghavi, Bertrand M. Hochwald

Proceedings of the 43rd Annual Conference on Information Sciences and Systems, 2009

Is it enough to drain the heaviest bottlenecks?

Gagan Raj Gupta, Sujay Sanghavi, Ness B. Shroff

Proceedings of the 47th Annual Allerton Conference on Communication, 2009

Sparse and low-rank matrix decompositions.

Venkat Chandrasekaran, Sujay Sanghavi, Pablo A. Parrilo, Alan S. Willsky

Proceedings of the 47th Annual Allerton Conference on Communication, 2009

2008

A New Mechanism for the Free-Rider Problem.

Sujay Sanghavi, Bruce E. Hajek

IEEE Trans. Autom. Control., 2008

Compressed sensing with sequential observations.

Dmitry M. Malioutov, Sujay Sanghavi, Alan S. Willsky

Proceedings of the IEEE International Conference on Acoustics, 2008

Networking sensors using belief propagation.

Sujay Sanghavi, Dmitry Malioutov, Alan S. Willsky

Proceedings of the 46th Annual Allerton Conference on Communication, 2008

2007

Gossiping With Multiple Messages.

Sujay Sanghavi, Bruce E. Hajek, Laurent Massoulié

IEEE Trans. Inf. Theory, 2007

Equivalence of LP Relaxation and Max-Product for Weighted Matching in General Graphs

Sujay Sanghavi

CoRR, 2007

Message Passing for Max-weight Independent Set.

Sujay Sanghavi, Devavrat Shah, Alan S. Willsky

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Linear programming analysis of loopy belief propagation for weighted matching.

Sujay Sanghavi, Dmitry M. Malioutov, Alan S. Willsky

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

2006

Decentralized Network Algorithms

Sujay Sanghavi

PhD thesis, 2006

Adaptive induced fluctuations for multiuser diversity.

Sujay Sanghavi, Bruce E. Hajek

IEEE Trans. Wirel. Commun., 2006

Intermediate Performance of Rateless Codes

Sujay Sanghavi

CoRR, 2006

2004

Optimal allocation of a divisible good to strategic buyers.

Sujay Sanghavi, Bruce E. Hajek

Proceedings of the 43rd IEEE Conference on Decision and Control, 2004