# H. Brendan McMahan

According to our database

Collaborative distances:

^{1}, H. Brendan McMahan authored at least 33 papers between 2003 and 2019.Collaborative distances:

## Timeline

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## Bibliography

2019

Semi-Cyclic Stochastic Gradient Descent.

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

2018

Graph Oracle Models, Lower Bounds, and Gaps for Parallel Stochastic Optimization.

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

cpSGD: Communication-efficient and differentially-private distributed SGD.

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

Learning Differentially Private Recurrent Language Models.

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

2017

A survey of Algorithms and Analysis for Adaptive Online Learning.

J. Mach. Learn. Res., 2017

Distributed Mean Estimation with Limited Communication.

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

On the Protection of Private Information in Machine Learning Systems: Two Recent Approches.

Proceedings of the 30th IEEE Computer Security Foundations Symposium, 2017

Practical Secure Aggregation for Privacy-Preserving Machine Learning.

Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security, CCS 2017, Dallas, TX, USA, October 30, 2017

Communication-Efficient Learning of Deep Networks from Decentralized Data.

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016

Deep Learning with Differential Privacy.

Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security, 2016

2014

Delay-Tolerant Algorithms for Asynchronous Distributed Online Learning.

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Unconstrained Online Linear Learning in Hilbert Spaces: Minimax Algorithms and Normal Approximations.

Proceedings of The 27th Conference on Learning Theory, 2014

2013

Minimax Optimal Algorithms for Unconstrained Linear Optimization.

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

Estimation, Optimization, and Parallelism when Data is Sparse.

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

Ad click prediction: a view from the trenches.

Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013

Large-Scale Learning with Less RAM via Randomization.

Proceedings of the 30th International Conference on Machine Learning, 2013

2012

Open Problem: Better Bounds for Online Logistic Regression.

Proceedings of the COLT 2012, 2012

No-Regret Algorithms for Unconstrained Online Convex Optimization.

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

2011

Follow-the-Regularized-Leader and Mirror Descent: Equivalence Theorems and L1 Regularization.

Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

Discussion of "Contextual Bandit Algorithms with Supervised Learning Guarantees".

Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

2010

Adaptive Bound Optimization for Online Convex Optimization.

Proceedings of the COLT 2010, 2010

2009

Sleeping Experts and Bandits with Stochastic Action Availability and Adversarial Rewards.

Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

Tighter Bounds for Multi-Armed Bandits with Expert Advice.

Proceedings of the COLT 2009, 2009

2007

A Fast Bundle-based Anytime Algorithm for Poker and other Convex Games.

Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007

Selecting Observations against Adversarial Objectives.

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

Efficiently computing minimax expected-size confidence regions.

Proceedings of the Machine Learning, 2007

A Unification of Extensive-Form Games and Markov Decision Processes.

Proceedings of the Twenty-Second AAAI Conference on Artificial Intelligence, 2007

2005

Online convex optimization in the bandit setting: gradient descent without a gradient.

Proceedings of the Sixteenth Annual ACM-SIAM Symposium on Discrete Algorithms, 2005

Bounded real-time dynamic programming: RTDP with monotone upper bounds and performance guarantees.

Proceedings of the Machine Learning, 2005

Fast Exact Planning in Markov Decision Processes.

Proceedings of the Fifteenth International Conference on Automated Planning and Scheduling (ICAPS 2005), 2005

2004

Multi-source spanning trees: algorithms for minimizing source eccentricities.

Discrete Applied Mathematics, 2004

Online Geometric Optimization in the Bandit Setting Against an Adaptive Adversary.

Proceedings of the Learning Theory, 17th Annual Conference on Learning Theory, 2004

2003

Planning in the Presence of Cost Functions Controlled by an Adversary.

Proceedings of the Machine Learning, 2003