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A Field Guide to Federated Optimization


Jul 14, 2021
Jianyu Wang, Zachary Charles, Zheng Xu, Gauri Joshi, H. Brendan McMahan, Blaise Aguera y Arcas, Maruan Al-Shedivat, Galen Andrew, Salman Avestimehr, Katharine Daly, Deepesh Data, Suhas Diggavi, Hubert Eichner, Advait Gadhikar, Zachary Garrett, Antonious M. Girgis, Filip Hanzely, Andrew Hard, Chaoyang He, Samuel Horvath, Zhouyuan Huo, Alex Ingerman, Martin Jaggi, Tara Javidi, Peter Kairouz, Satyen Kale, Sai Praneeth Karimireddy, Jakub Konecny, Sanmi Koyejo, Tian Li, Luyang Liu, Mehryar Mohri, Hang Qi, Sashank J. Reddi, Peter Richtarik, Karan Singhal, Virginia Smith, Mahdi Soltanolkotabi, Weikang Song, Ananda Theertha Suresh, Sebastian U. Stich, Ameet Talwalkar, Hongyi Wang, Blake Woodworth, Shanshan Wu, Felix X. Yu, Honglin Yuan, Manzil Zaheer, Mi Zhang, Tong Zhang, Chunxiang Zheng, Chen Zhu, Wennan Zhu


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Federated Reconstruction: Partially Local Federated Learning


Feb 18, 2021
Karan Singhal, Hakim Sidahmed, Zachary Garrett, Shanshan Wu, Keith Rush, Sushant Prakash


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Implicit Regularization of Normalization Methods


Nov 23, 2019
Xiaoxia Wu, Edgar Dobriban, Tongzheng Ren, Shanshan Wu, Zhiyuan Li, Suriya Gunasekar, Rachel Ward, Qiang Liu


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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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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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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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Leveraging Sparsity for Efficient Submodular Data Summarization


Mar 08, 2017
Erik M. Lindgren, Shanshan Wu, Alexandros G. Dimakis

* In NIPS 2016 

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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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