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Mime: Mimicking Centralized Stochastic Algorithms in Federated Learning

Aug 08, 2020
Sai Praneeth Karimireddy, Martin Jaggi, Satyen Kale, Mehryar Mohri, Sashank J. Reddi, Sebastian U. Stich, Ananda Theertha Suresh


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$O(n)$ Connections are Expressive Enough: Universal Approximability of Sparse Transformers

Jun 08, 2020
Chulhee Yun, Yin-Wen Chang, Srinadh Bhojanapalli, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar

* 32 pages 

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Why distillation helps: a statistical perspective

May 21, 2020
Aditya Krishna Menon, Ankit Singh Rawat, Sashank J. Reddi, Seungyeon Kim, Sanjiv Kumar


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Doubly-stochastic mining for heterogeneous retrieval

Apr 23, 2020
Ankit Singh Rawat, Aditya Krishna Menon, Andreas Veit, Felix Yu, Sashank J. Reddi, Sanjiv Kumar


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Low-Rank Bottleneck in Multi-head Attention Models

Feb 17, 2020
Srinadh Bhojanapalli, Chulhee Yun, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar

* 17 pages, 4 figures 

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Are Transformers universal approximators of sequence-to-sequence functions?

Dec 20, 2019
Chulhee Yun, Srinadh Bhojanapalli, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar

* Accepted to ICLR 2020 

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SCAFFOLD: Stochastic Controlled Averaging for On-Device Federated Learning

Oct 14, 2019
Sai Praneeth Karimireddy, Satyen Kale, Mehryar Mohri, Sashank J. Reddi, Sebastian U. Stich, Ananda Theertha Suresh


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AdaCliP: Adaptive Clipping for Private SGD

Aug 20, 2019
Venkatadheeraj Pichapati, Ananda Theertha Suresh, Felix X. Yu, Sashank J. Reddi, Sanjiv Kumar

* 18 pages 

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On the Convergence of Adam and Beyond

Apr 19, 2019
Sashank J. Reddi, Satyen Kale, Sanjiv Kumar

* Appeared in ICLR 2018 

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Escaping Saddle Points with Adaptive Gradient Methods

Jan 26, 2019
Matthew Staib, Sashank J. Reddi, Satyen Kale, Sanjiv Kumar, Suvrit Sra


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Stochastic Negative Mining for Learning with Large Output Spaces

Oct 16, 2018
Sashank J. Reddi, Satyen Kale, Felix Yu, Dan Holtmann-Rice, Jiecao Chen, Sanjiv Kumar


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Riemannian SVRG: Fast Stochastic Optimization on Riemannian Manifolds

Apr 07, 2017
Hongyi Zhang, Sashank J. Reddi, Suvrit Sra

* Advances in Neural Information Processing Systems 29 (NIPS 2016) 
* This is the final version that appeared in NIPS 2016. Our proof of Lemma 2 was incorrect in the previous arXiv version. (9 pages paper + 6 pages appendix) 

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AIDE: Fast and Communication Efficient Distributed Optimization

Aug 24, 2016
Sashank J. Reddi, Jakub Kone膷n媒, Peter Richt谩rik, Barnab谩s P贸cz贸s, Alex Smola


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Stochastic Frank-Wolfe Methods for Nonconvex Optimization

Jul 29, 2016
Sashank J. Reddi, Suvrit Sra, Barnabas Poczos, Alex Smola


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Fast Stochastic Methods for Nonsmooth Nonconvex Optimization

May 23, 2016
Sashank J. Reddi, Suvrit Sra, Barnabas Poczos, Alex Smola


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Stochastic Variance Reduction for Nonconvex Optimization

Apr 04, 2016
Sashank J. Reddi, Ahmed Hefny, Suvrit Sra, Barnabas Poczos, Alex Smola

* Minor feedback changes 

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Fast Incremental Method for Nonconvex Optimization

Mar 19, 2016
Sashank J. Reddi, Suvrit Sra, Barnabas Poczos, Alex Smola


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On Variance Reduction in Stochastic Gradient Descent and its Asynchronous Variants

Jan 25, 2016
Sashank J. Reddi, Ahmed Hefny, Suvrit Sra, Barnab谩s P贸czos, Alex Smola


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Adaptivity and Computation-Statistics Tradeoffs for Kernel and Distance based High Dimensional Two Sample Testing

Aug 04, 2015
Aaditya Ramdas, Sashank J. Reddi, Barnabas Poczos, Aarti Singh, Larry Wasserman

* 35 pages, 4 figures 

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On the Decreasing Power of Kernel and Distance based Nonparametric Hypothesis Tests in High Dimensions

Nov 24, 2014
Sashank J. Reddi, Aaditya Ramdas, Barnab谩s P贸czos, Aarti Singh, Larry Wasserman

* 19 pages, 9 figures, published in AAAI-15: The 29th AAAI Conference on Artificial Intelligence (with author order reversed from ArXiv) 

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On the High-dimensional Power of Linear-time Kernel Two-Sample Testing under Mean-difference Alternatives

Nov 23, 2014
Aaditya Ramdas, Sashank J. Reddi, Barnabas Poczos, Aarti Singh, Larry Wasserman

* 25 pages, 5 figures 

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A Maximum Likelihood Approach For Selecting Sets of Alternatives

Oct 16, 2012
Ariel D. Procaccia, Sashank J. Reddi, Nisarg Shah

* Appears in Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence (UAI2012) 

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