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Robust Training in High Dimensions via Block Coordinate Geometric Median Descent


Jun 16, 2021
Anish Acharya, Abolfazl Hashemi, Prateek Jain, Sujay Sanghavi, Inderjit S. Dhillon, Ufuk Topcu


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


Jun 13, 2021
Rudrajit Das, Abolfazl Hashemi, Sujay Sanghavi, Inderjit S. Dhillon


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


Jun 01, 2021
Tavor Z. Baharav, Daniel L. Jiang, Kedarnath Kolluri, Sujay Sanghavi, Inderjit S. Dhillon


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Nearly Horizon-Free Offline Reinforcement Learning


Mar 25, 2021
Tongzheng Ren, Jialian Li, Bo Dai, Simon S. Du, Sujay Sanghavi


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Combinatorial Bandits without Total Order for Arms


Mar 03, 2021
Shuo Yang, Tongzheng Ren, Inderjit S. Dhillon, Sujay Sanghavi


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Linear Bandit Algorithms with Sublinear Time Complexity


Mar 03, 2021
Shuo Yang, Tongzheng Ren, Sanjay Shakkottai, Eric Price, Inderjit S. Dhillon, Sujay Sanghavi


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Improved Convergence Rates for Non-Convex Federated Learning with Compression


Dec 12, 2020
Rudrajit Das, Abolfazl Hashemi, Sujay Sanghavi, Inderjit S. Dhillon


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On Generalization of Adaptive Methods for Over-parameterized Linear Regression


Nov 28, 2020
Vatsal Shah, Soumya Basu, Anastasios Kyrillidis, Sujay Sanghavi

* arXiv admin note: substantial text overlap with arXiv:1811.07055 

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


Nov 20, 2020
Abolfazl Hashemi, Anish Acharya, Rudrajit Das, Haris Vikalo, Sujay Sanghavi, Inderjit Dhillon


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Extreme Multi-label Classification from Aggregated Labels


Apr 01, 2020
Yanyao Shen, Hsiang-fu Yu, Sujay Sanghavi, Inderjit Dhillon


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Choosing the Sample with Lowest Loss makes SGD Robust


Jan 10, 2020
Vatsal Shah, Xiaoxia Wu, Sujay Sanghavi


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


Nov 08, 2019
Shuo Yang, Yanyao Shen, Sujay Sanghavi

* Accepted by NeurIPS 2019 

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Learning Distributions Generated by One-Layer ReLU Networks


Sep 19, 2019
Shanshan Wu, Alexandros G. Dimakis, Sujay Sanghavi

* NeurIPS 2019 

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Blocking Bandits


Jul 27, 2019
Soumya Basu, Rajat Sen, Sujay Sanghavi, Sanjay Shakkottai


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Iterative Least Trimmed Squares for Mixed Linear Regression


Feb 10, 2019
Yanyao Shen, Sujay Sanghavi


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Minimum norm solutions do not always generalize well for over-parameterized problems


Nov 16, 2018
Vatsal Shah, Anastasios Kyrillidis, Sujay Sanghavi


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Sparse Logistic Regression Learns All Discrete Pairwise Graphical Models


Oct 28, 2018
Shanshan Wu, Sujay Sanghavi, Alexandros G. Dimakis

* 29 pages, 3 figures 

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Iteratively Learning from the Best


Oct 28, 2018
Yanyao Shen, Sujay Sanghavi


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The Sparse Recovery Autoencoder


Jul 05, 2018
Shanshan Wu, Alexandros G. Dimakis, Sujay Sanghavi, Felix X. Yu, Daniel Holtmann-Rice, Dmitry Storcheus, Afshin Rostamizadeh, Sanjiv Kumar

* 23 pages, 8 figures 

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Searching for a Single Community in a Graph


May 24, 2018
Avik Ray, Sujay Sanghavi, Sanjay Shakkottai

* ACM Journal on Modeling and Performance Evaluation of Computing Systems (TOMPECS) [to appear] 

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The Search Problem in Mixture Models


Feb 24, 2018
Avik Ray, Joe Neeman, Sujay Sanghavi, Sanjay Shakkottai


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Sparse Quadratic Logistic Regression in Sub-quadratic Time


Mar 08, 2017
Karthikeyan Shanmugam, Murat Kocaoglu, Alexandros G. Dimakis, Sujay Sanghavi


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Finding Low-Rank Solutions via Non-Convex Matrix Factorization, Efficiently and Provably


Oct 29, 2016
Dohyung Park, Anastasios Kyrillidis, Constantine Caramanis, Sujay Sanghavi

* 45 pages 

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Single Pass PCA of Matrix Products


Oct 26, 2016
Shanshan Wu, Srinadh Bhojanapalli, Sujay Sanghavi, Alexandros G. Dimakis

* 24 pages, 4 figures, NIPS 2016 

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Provable Burer-Monteiro factorization for a class of norm-constrained matrix problems


Oct 01, 2016
Dohyung Park, Anastasios Kyrillidis, Srinadh Bhojanapalli, Constantine Caramanis, Sujay Sanghavi

* 28 pages 

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


Sep 27, 2016
Dohyung Park, Anastasios Kyrillidis, Constantine Caramanis, Sujay Sanghavi

* 14 pages, no figures 

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


Aug 19, 2016
Xinyang Yi, Constantine Caramanis, Sujay Sanghavi

* 39 pages, 2 figures 

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The local convexity of solving systems of quadratic equations


Jun 01, 2016
Chris D. White, Sujay Sanghavi, Rachel Ward

* 36 pages, 3 figures 

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Matrix completion with column manipulation: Near-optimal sample-robustness-rank tradeoffs


Apr 24, 2016
Yudong Chen, Huan Xu, Constantine Caramanis, Sujay Sanghavi

* IEEE Transactions on Information Theory, vol. 62, no. 1, pp. 503-526, 2016 
* This is the journal version of the paper with additional results 

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