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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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Estimating Training Data Influence by Tracking Gradient Descent

Feb 19, 2020
Garima Pruthi, Frederick Liu, Mukund Sundararajan, Satyen Kale


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A Deep Conditioning Treatment of Neural Networks

Feb 04, 2020
Naman Agarwal, Pranjal Awasthi, Satyen Kale


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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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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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Hypothesis Set Stability and Generalization

Apr 17, 2019
Dylan J. Foster, Spencer Greenberg, Satyen Kale, Haipeng Luo, Mehryar Mohri, Karthik Sridharan


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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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Online Learning of Quantum States

Oct 01, 2018
Scott Aaronson, Xinyi Chen, Elad Hazan, Satyen Kale, Ashwin Nayak

* 17 pages 

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Logistic Regression: The Importance of Being Improper

Mar 25, 2018
Dylan J. Foster, Satyen Kale, Haipeng Luo, Mehryar Mohri, Karthik Sridharan


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Parameter-free online learning via model selection

Jan 03, 2018
Dylan J. Foster, Satyen Kale, Mehryar Mohri, Karthik Sridharan

* NIPS 2017 

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Adaptive Feature Selection: Computationally Efficient Online Sparse Linear Regression under RIP

Jun 14, 2017
Satyen Kale, Zohar Karnin, Tengyuan Liang, Dávid Pál

* Appearing in 34th International Conference on Machine Learning (ICML), 2017 

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Hardness of Online Sleeping Combinatorial Optimization Problems

Dec 19, 2016
Satyen Kale, Chansoo Lee, Dávid Pál

* A version of this paper was published in NIPS 2016 

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Online Sparse Linear Regression

Mar 07, 2016
Dean Foster, Satyen Kale, Howard Karloff


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Online Gradient Boosting

Oct 30, 2015
Alina Beygelzimer, Elad Hazan, Satyen Kale, Haipeng Luo


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Optimal and Adaptive Algorithms for Online Boosting

Feb 09, 2015
Alina Beygelzimer, Satyen Kale, Haipeng Luo


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Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits

Oct 14, 2014
Alekh Agarwal, Daniel Hsu, Satyen Kale, John Langford, Lihong Li, Robert E. Schapire


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Multiarmed Bandits With Limited Expert Advice

Jul 08, 2013
Satyen Kale

* Updated with tighter upper bound based on PolyINF algorithm, lower bound nearly matching the upper bound, and fixed some typos 

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Bargaining for Revenue Shares on Tree Trading Networks

Apr 22, 2013
Arpita Ghosh, Satyen Kale, Kevin Lang, Benjamin Moseley

* An extended abstract of this paper appears in Proceedings of IJCAI 2013 

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Efficient and Practical Stochastic Subgradient Descent for Nuclear Norm Regularization

Jun 27, 2012
Haim Avron, Satyen Kale, Shiva Kasiviswanathan, Vikas Sindhwani

* Appears in Proceedings of the 29th International Conference on Machine Learning (ICML 2012) 

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Projection-free Online Learning

Jun 18, 2012
Elad Hazan, Satyen Kale

* ICML2012 

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Near-Optimal Algorithms for Online Matrix Prediction

Mar 31, 2012
Elad Hazan, Satyen Kale, Shai Shalev-Shwartz

* 25 pages 

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Contextual Bandit Learning with Predictable Rewards

Mar 02, 2012
Alekh Agarwal, Miroslav DudĂ­k, Satyen Kale, John Langford, Robert E. Schapire


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Efficient Optimal Learning for Contextual Bandits

Jun 13, 2011
Miroslav Dudik, Daniel Hsu, Satyen Kale, Nikos Karampatziakis, John Langford, Lev Reyzin, Tong Zhang


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