Satyen Kale

According to our database, Satyen Kale authored at least 99 papers between 2004 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

On the Unreasonable Effectiveness of Federated Averaging with Heterogeneous Data.

Jianyu Wang, Rudrajit Das, Gauri Joshi, Satyen Kale, Zheng Xu, Tong Zhang

Trans. Mach. Learn. Res., 2024

Stacking as Accelerated Gradient Descent.

Naman Agarwal, Pranjal Awasthi, Satyen Kale, Eric Zhao

CoRR, 2024

Efficient Stagewise Pretraining via Progressive Subnetworks.

Abhishek Panigrahi, Nikunj Saunshi, Kaifeng Lyu, Sobhan Miryoosefi, Sashank J. Reddi, Satyen Kale, Sanjiv Kumar

CoRR, 2024

Asynchronous Local-SGD Training for Language Modeling.

Bo Liu, Rachita Chhaparia, Arthur Douillard, Satyen Kale, Andrei A. Rusu, Jiajun Shen, Arthur Szlam, Marc'Aurelio Ranzato

CoRR, 2024

Improved Differentially Private and Lazy Online Convex Optimization: Lower Regret without Smoothness Requirements.

Naman Agarwal, Satyen Kale, Karan Singh, Abhradeep Guha Thakurta

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Semi-supervised Group DRO: Combating Sparsity with Unlabeled Data.

Pranjal Awasthi, Satyen Kale, Ankit Pensia

Proceedings of the International Conference on Algorithmic Learning Theory, 2024

2023

Improved Differentially Private and Lazy Online Convex Optimization.

Naman Agarwal, Satyen Kale, Karan Singh, Abhradeep Guha Thakurta

CoRR, 2023

Improved Differentially Private Densest Subgraph: Local and Purely Additive.

Michael Dinitz, Satyen Kale, Silvio Lattanzi, Sergei Vassilvitskii

CoRR, 2023

Efficient Training of Language Models using Few-Shot Learning.

Sashank J. Reddi, Sobhan Miryoosefi, Stefani Karp, Shankar Krishnan, Satyen Kale, Seungyeon Kim, Sanjiv Kumar

Proceedings of the International Conference on Machine Learning, 2023

Beyond Uniform Lipschitz Condition in Differentially Private Optimization.

Rudrajit Das, Satyen Kale, Zheng Xu, Tong Zhang, Sujay Sanghavi

Proceedings of the International Conference on Machine Learning, 2023

On the Convergence of Federated Averaging with Cyclic Client Participation.

Yae Jee Cho, Pranay Sharma, Gauri Joshi, Zheng Xu, Satyen Kale, Tong Zhang

Proceedings of the International Conference on Machine Learning, 2023

Differentially Private and Lazy Online Convex Optimization.

Naman Agarwal, Satyen Kale, Karan Singh, Abhradeep Thakurta

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

2022

Mixed Federated Learning: Joint Decentralized and Centralized Learning.

Sean Augenstein, Andrew Hard, Lin Ning, Karan Singhal, Satyen Kale, Kurt Partridge, Rajiv Mathews

CoRR, 2022

From Gradient Flow on Population Loss to Learning with Stochastic Gradient Descent.

Christopher De Sa, Satyen Kale, Jason D. Lee, Ayush Sekhari, Karthik Sridharan

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Reproducibility in Optimization: Theoretical Framework and Limits.

Kwangjun Ahn, Prateek Jain, Ziwei Ji, Satyen Kale, Praneeth Netrapalli, Gil I. Shamir

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Agnostic Learnability of Halfspaces via Logistic Loss.

Ziwei Ji, Kwangjun Ahn, Pranjal Awasthi, Satyen Kale, Stefani Karp

Proceedings of the International Conference on Machine Learning, 2022

Pushing the Efficiency-Regret Pareto Frontier for Online Learning of Portfolios and Quantum States.

Julian Zimmert, Naman Agarwal, Satyen Kale

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

Self-Consistency of the Fokker Planck Equation.

Zebang Shen, Zhenfu Wang, Satyen Kale, Alejandro Ribeiro, Amin Karbasi, Hamed Hassani

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

Private Matrix Approximation and Geometry of Unitary Orbits.

Oren Mangoubi, Yikai Wu, Satyen Kale, Abhradeep Thakurta, Nisheeth K. Vishnoi

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

Efficient Methods for Online Multiclass Logistic Regression.

Naman Agarwal, Satyen Kale, Julian Zimmert

Proceedings of the International Conference on Algorithmic Learning Theory, 29 March, 2022

Federated Functional Gradient Boosting.

Zebang Shen, Hamed Hassani, Satyen Kale, Amin Karbasi

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

A Field Guide to Federated Optimization.

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

CoRR, 2021

A Multiclass Boosting Framework for Achieving Fast and Provable Adversarial Robustness.

Jacob D. Abernethy, Pranjal Awasthi, Satyen Kale

CoRR, 2021

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

Ayush Sekhari, Karthik Sridharan, Satyen Kale

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning with User-Level Privacy.

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

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Breaking the centralized barrier for cross-device federated learning.

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

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

A Deep Conditioning Treatment of Neural Networks.

Naman Agarwal, Pranjal Awasthi, Satyen Kale

Proceedings of the Algorithmic Learning Theory, 2021

2020

Mime: Mimicking Centralized Stochastic Algorithms in Federated Learning.

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

CoRR, 2020

Estimating Training Data Influence by Tracking Gradient Descent.

Garima Pruthi, Frederick Liu, Mukund Sundararajan, Satyen Kale

CoRR, 2020

Estimating Training Data Influence by Tracing Gradient Descent.

Garima Pruthi, Frederick Liu, Satyen Kale, Mukund Sundararajan

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

PAC-Bayes Learning Bounds for Sample-Dependent Priors.

Pranjal Awasthi, Satyen Kale, Stefani Karp, Mehryar Mohri

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

SCAFFOLD: Stochastic Controlled Averaging for Federated Learning.

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

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

SCAFFOLD: Stochastic Controlled Averaging for On-Device Federated Learning.

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

CoRR, 2019

Breaking the Glass Ceiling for Embedding-Based Classifiers for Large Output Spaces.

Chuan Guo, Ali Mousavi, Xiang Wu, Daniel Niels Holtmann-Rice, Satyen Kale, Sashank J. Reddi, Sanjiv Kumar

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Hypothesis Set Stability and Generalization.

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

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Escaping Saddle Points with Adaptive Gradient Methods.

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

Proceedings of the 36th International Conference on Machine Learning, 2019

Algorithmic Learning Theory 2019: Preface.

Aurélien Garivier, Satyen Kale

Proceedings of the Algorithmic Learning Theory, 2019

Stochastic Negative Mining for Learning with Large Output Spaces.

Sashank J. Reddi, Satyen Kale, Felix X. Yu, Daniel Niels Holtmann-Rice, Jiecao Chen, Sanjiv Kumar

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Adaptive Methods for Nonconvex Optimization.

Manzil Zaheer, Sashank J. Reddi, Devendra Singh Sachan, Satyen Kale, Sanjiv Kumar

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Online Learning of Quantum States.

Scott Aaronson, Xinyi Chen, Elad Hazan, Satyen Kale, Ashwin Nayak

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Loss Decomposition for Fast Learning in Large Output Spaces.

Ian En-Hsu Yen, Satyen Kale, Felix X. Yu, Daniel Niels Holtmann-Rice, Sanjiv Kumar, Pradeep Ravikumar

Proceedings of the 35th International Conference on Machine Learning, 2018

On the Convergence of Adam and Beyond.

Sashank J. Reddi, Satyen Kale, Sanjiv Kumar

Proceedings of the 6th International Conference on Learning Representations, 2018

Logistic Regression: The Importance of Being Improper.

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

Proceedings of the Conference On Learning Theory, 2018

2017

Near-Optimal Algorithms for Online Matrix Prediction.

Elad Hazan, Satyen Kale, Shai Shalev-Shwartz

SIAM J. Comput., 2017

Parameter-Free Online Learning via Model Selection.

Dylan J. Foster, Satyen Kale, Mehryar Mohri, Karthik Sridharan

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

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

Satyen Kale, Zohar S. Karnin, Tengyuan Liang, Dávid Pál

Proceedings of the 34th International Conference on Machine Learning, 2017

Preface: Conference on Learning Theory (COLT), 2017.

Satyen Kale, Ohad Shamir

Proceedings of the 30th Conference on Learning Theory, 2017

2016

Learning rotations with little regret.

Elad Hazan, Satyen Kale, Manfred K. Warmuth

Mach. Learn., 2016

A Combinatorial, Primal-Dual Approach to Semidefinite Programs.

Sanjeev Arora, Satyen Kale

J. ACM, 2016

Hardness of Online Sleeping Combinatorial Optimization Problems.

Satyen Kale, Chansoo Lee, Dávid Pál

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Online Semidefinite Programming.

Noa Elad, Satyen Kale, Joseph (Seffi) Naor

Proceedings of the 43rd International Colloquium on Automata, Languages, and Programming, 2016

Online Sparse Linear Regression.

Dean P. Foster, Satyen Kale, Howard J. Karloff

Proceedings of the 29th Conference on Learning Theory, 2016

2015

Online Gradient Boosting.

Alina Beygelzimer, Elad Hazan, Satyen Kale, Haipeng Luo

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Optimal and Adaptive Algorithms for Online Boosting.

Alina Beygelzimer, Satyen Kale, Haipeng Luo

Proceedings of the 32nd International Conference on Machine Learning, 2015

Budgeted Prediction with Expert Advice.

Kareem Amin, Satyen Kale, Gerald Tesauro, Deepak S. Turaga

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014

Beyond the regret minimization barrier: optimal algorithms for stochastic strongly-convex optimization.

Elad Hazan, Satyen Kale

J. Mach. Learn. Res., 2014

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

Alekh Agarwal, Daniel J. Hsu, Satyen Kale, John Langford, Lihong Li, Robert E. Schapire

Proceedings of the 31th International Conference on Machine Learning, 2014

Open Problem: Efficient Online Sparse Regression.

Satyen Kale

Proceedings of The 27th Conference on Learning Theory, 2014

Multiarmed Bandits With Limited Expert Advice.

Satyen Kale

Proceedings of The 27th Conference on Learning Theory, 2014

2013

Noise Tolerance of Expanders and Sublinear Expansion Reconstruction.

Satyen Kale, Yuval Peres, C. Seshadhri

SIAM J. Comput., 2013

Adaptive Market Making via Online Learning.

Jacob D. Abernethy, Satyen Kale

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Bargaining for Revenue Shares on Tree Trading Networks.

Arpita Ghosh, Satyen Kale, Kevin J. Lang, Benjamin Moseley

Proceedings of the IJCAI 2013, 2013

The Approximability of the Binary Paintshop Problem.

Anupam Gupta, Satyen Kale, Viswanath Nagarajan, Rishi Saket, Baruch Schieber

Proceedings of the Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques, 2013

2012

The Multiplicative Weights Update Method: a Meta-Algorithm and Applications.

Sanjeev Arora, Elad Hazan, Satyen Kale

Theory Comput., 2012

Commentary on "Online Optimization with Gradual Variations".

Satyen Kale

Proceedings of the COLT 2012, 2012

Online submodular minimization.

Elad Hazan, Satyen Kale

J. Mach. Learn. Res., 2012

Contextual Bandit Learning with Predictable Rewards.

Alekh Agarwal, Miroslav Dudík, Satyen Kale, John Langford, Robert E. Schapire

Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Projection-free Online Learning.

Elad Hazan, Satyen Kale

Proceedings of the 29th International Conference on Machine Learning, 2012

Efficient and Practical Stochastic Subgradient Descent for Nuclear Norm Regularization.

Haim Avron, Satyen Kale, Shiva Prasad Kasiviswanathan, Vikas Sindhwani

Proceedings of the 29th International Conference on Machine Learning, 2012

2011

An Expansion Tester for Bounded Degree Graphs.

Satyen Kale, C. Seshadhri

SIAM J. Comput., 2011

A simple multi-armed bandit algorithm with optimal variation-bounded regret.

Elad Hazan, Satyen Kale

Proceedings of the COLT 2011, 2011

Beyond the regret minimization barrier: an optimal algorithm for stochastic strongly-convex optimization.

Elad Hazan, Satyen Kale

Proceedings of the COLT 2011, 2011

Better Algorithms for Benign Bandits.

Elad Hazan, Satyen Kale

J. Mach. Learn. Res., 2011

Efficient Optimal Learning for Contextual Bandits.

Miroslav Dudík, Daniel J. Hsu, Satyen Kale, Nikos Karampatziakis, John Langford, Lev Reyzin, Tong Zhang

Proceedings of the UAI 2011, 2011

Who moderates the moderators?: crowdsourcing abuse detection in user-generated content.

Arpita Ghosh, Satyen Kale, R. Preston McAfee

Proceedings of the Proceedings 12th ACM Conference on Electronic Commerce (EC-2011), 2011

Newtron: an Efficient Bandit algorithm for Online Multiclass Prediction.

Elad Hazan, Satyen Kale

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Combinatorial Approximation Algorithms for MaxCut using Random Walks.

Satyen Kale, C. Seshadhri

Proceedings of the Innovations in Computer Science, 2011

Cross-Validation and Mean-Square Stability.

Satyen Kale, Ravi Kumar, Sergei Vassilvitskii

Proceedings of the Innovations in Computer Science, 2011

2010

O(sqrt(log(n)) Approximation to SPARSEST CUT in Õ(n²) Time.

Sanjeev Arora, Elad Hazan, Satyen Kale

SIAM J. Comput., 2010

Extracting certainty from uncertainty: regret bounded by variation in costs.

Elad Hazan, Satyen Kale

Mach. Learn., 2010

Non-Stochastic Bandit Slate Problems.

Satyen Kale, Lev Reyzin, Robert E. Schapire

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

On-line Variance Minimization in O(n2) per Trial?

Elad Hazan, Satyen Kale, Manfred K. Warmuth

Proceedings of the COLT 2010, 2010

2009

The uniform hardcore lemma via approximate Bregman projections.

Boaz Barak, Moritz Hardt, Satyen Kale

Proceedings of the Twentieth Annual ACM-SIAM Symposium on Discrete Algorithms, 2009

On Stochastic and Worst-case Models for Investing.

Elad Hazan, Satyen Kale

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Beyond Convexity: Online Submodular Minimization.

Elad Hazan, Satyen Kale

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

2008

Noise Tolerance of Expanders and Sublinear Expander Reconstruction.

Satyen Kale, Yuval Peres, C. Seshadhri

Proceedings of the 49th Annual IEEE Symposium on Foundations of Computer Science, 2008

2007

Logarithmic regret algorithms for online convex optimization.

Elad Hazan, Amit Agarwal, Satyen Kale

Mach. Learn., 2007

A variation on SVD based image compression.

Abhiram G. Ranade, Srikanth S. Mahabalarao, Satyen Kale

Image Vis. Comput., 2007

Testing Expansion in Bounded Degree Graphs.

Satyen Kale, C. Seshadhri

Electron. Colloquium Comput. Complex., 2007

Boosting and hard-core set constructions: a simplified approach.

Satyen Kale

Electron. Colloquium Comput. Complex., 2007

Efficient aggregation algorithms for probabilistic data.

T. S. Jayram, Satyen Kale, Erik Vee

Proceedings of the Eighteenth Annual ACM-SIAM Symposium on Discrete Algorithms, 2007

Privacy, accuracy, and consistency too: a holistic solution to contingency table release.

Boaz Barak, Kamalika Chaudhuri, Cynthia Dwork, Satyen Kale, Frank McSherry, Kunal Talwar

Proceedings of the Twenty-Sixth ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, 2007

Computational Equivalence of Fixed Points and No Regret Algorithms, and Convergence to Equilibria.

Elad Hazan, Satyen Kale

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

2006

Algorithms for portfolio management based on the Newton method.

Amit Agarwal, Elad Hazan, Satyen Kale, Robert E. Schapire

Proceedings of the Machine Learning, 2006

Logarithmic Regret Algorithms for Online Convex Optimization.

Elad Hazan, Adam Kalai, Satyen Kale, Amit Agarwal

Proceedings of the Learning Theory, 19th Annual Conference on Learning Theory, 2006

A Fast Random Sampling Algorithm for Sparsifying Matrices.

Sanjeev Arora, Elad Hazan, Satyen Kale

Proceedings of the Approximation, 2006

2005

Analysis and Algorithms for Content-Based Event Matching.

Satyen Kale, Elad Hazan, Fengyun Cao, Jaswinder Pal Singh

Proceedings of the 25th International Conference on Distributed Computing Systems Workshops (ICDCS 2005 Workshops), 2005

Fast Algorithms for Approximate Semide.nite Programming using the Multiplicative Weights Update Method.

Sanjeev Arora, Elad Hazan, Satyen Kale

Proceedings of the 46th Annual IEEE Symposium on Foundations of Computer Science (FOCS 2005), 2005

2004

0(sqrt (log n)) Approximation to SPARSEST CUT in Õ(n²) Time.

Sanjeev Arora, Elad Hazan, Satyen Kale

Proceedings of the 45th Symposium on Foundations of Computer Science (FOCS 2004), 2004