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Efficient Methods for Online Multiclass Logistic Regression


Oct 10, 2021
Naman Agarwal, Satyen Kale, Julian Zimmert


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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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SGD: The Role of Implicit Regularization, Batch-size and Multiple-epochs


Jul 11, 2021
Satyen Kale, Ayush Sekhari, Karthik Sridharan


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Federated Functional Gradient Boosting


Mar 11, 2021
Zebang Shen, Hamed Hassani, Satyen Kale, Amin Karbasi


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A Multiclass Boosting Framework for Achieving Fast and Provable Adversarial Robustness


Mar 03, 2021
Jacob Abernethy, Pranjal Awasthi, Satyen Kale

* Fixed misspelled first author name 

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Learning with User-Level Privacy


Mar 02, 2021
Daniel Levy, Ziteng Sun, Kareem Amin, Satyen Kale, Alex Kulesza, Mehryar Mohri, Ananda Theertha Suresh

* 39 pages, 0 figure 

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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 Dudík, Satyen Kale, John Langford, Robert E. Schapire


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