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Gaussian MRF Covariance Modeling for Efficient Black-Box Adversarial Attacks

Oct 08, 2020
Anit Kumar Sahu, Satya Narayan Shukla, J. Zico Kolter


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Hard Label Black-box Adversarial Attacks in Low Query Budget Regimes

Jul 13, 2020
Satya Narayan Shukla, Anit Kumar Sahu, Devin Willmott, J. Zico Kolter

* arXiv admin note: substantial text overlap with arXiv:1909.13857 

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FedDANE: A Federated Newton-Type Method

Jan 07, 2020
Tian Li, Anit Kumar Sahu, Manzil Zaheer, Maziar Sanjabi, Ameet Talwalkar, Virginia Smith

* Asilomar Conference on Signals, Systems, and Computers 2019 

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Black-box Adversarial Attacks with Bayesian Optimization

Sep 30, 2019
Satya Narayan Shukla, Anit Kumar Sahu, Devin Willmott, J. Zico Kolter


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Learning in Confusion: Batch Active Learning with Noisy Oracle

Sep 27, 2019
Gaurav Gupta, Anit Kumar Sahu, Wan-Yi Lin


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Federated Learning: Challenges, Methods, and Future Directions

Aug 21, 2019
Tian Li, Anit Kumar Sahu, Ameet Talwalkar, Virginia Smith


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MATCHA: Speeding Up Decentralized SGD via Matching Decomposition Sampling

May 23, 2019
Jianyu Wang, Anit Kumar Sahu, Zhouyi Yang, Gauri Joshi, Soummya Kar


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Distributed stochastic optimization with gradient tracking over strongly-connected networks

Apr 09, 2019
Ran Xin, Anit Kumar Sahu, Usman A. Khan, Soummya Kar


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On the Convergence of Federated Optimization in Heterogeneous Networks

Dec 14, 2018
Anit Kumar Sahu, Tian Li, Maziar Sanjabi, Manzil Zaheer, Ameet Talwalkar, Virginia Smith

* Preprint. Work in Progress 

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Managing App Install Ad Campaigns in RTB: A Q-Learning Approach

Nov 11, 2018
Anit Kumar Sahu, Shaunak Mishra, Narayan Bhamidipati

* 6 pages 

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Towards Gradient Free and Projection Free Stochastic Optimization

Oct 09, 2018
Anit Kumar Sahu, Manzil Zaheer, Soummya Kar

* 21 pages, 3 figures 

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