H. Brendan McMahan
14 papers · 1999–2023 · 7 venues · across top CS/AI venues
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Achievements
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π£ Hot Topic Early Bird π Conference Polyglot Β· Silver π Academic Marathon Β· Ultra π Interdisciplinary Bridge Β· Silver πΊοΈ Taxonomy Completionist (20)
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Trend Setter
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Conference Pioneer
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Century Club Β· Bronze
Top co-authors
Research topics
Machine Learning
(11)
Application Areas
(7)
Optimization & Theory
(6)
Artificial Intelligence
(4)
Mathematics & Optimization
(4)
Learning Paradigms Β· Artificial Intelligence
(4)
Optimization
(4)
Learning Types
(3)
Deep Learning
(2)
Security & Privacy
(2)
Core Methods
(2)
Differential Privacy
(2)
Computer Science
(1)
Learning Paradigms Β· Machine Learning
(1)
Models
(1)
Keywords
differential privacy
(6)
federated learning
(6)
regret bound
(3)
matrix factorization
(2)
privacy amplification
(2)
recurrent neural network
(2)
user-level privacy
(2)
online learning
(1)
mean estimation
(1)
robust optimization
(1)
distributed learning
(1)
adaptive learning
(1)
hilbert space
(1)
gradient descent
(1)
dual averaging
(1)
stochastic gradient descent
(1)
active selection
(1)
sensor placement
(1)
convex optimization
(1)
experimental design
(1)
Papers
(Amplified) Banded Matrix Factorization: A unified approach to private training
NeurIPS 2023
Gradient Descent with Linearly Correlated Noise: Theory and Applications to Differential Privacy
NeurIPS 2023
Learning To Generate Image Embeddings With User-Level Differential Privacy
CVPR 2023
Unleashing the Power of Randomization in Auditing Differentially Private ML
NeurIPS 2023
Improved Differential Privacy for SGD via Optimal Private Linear Operators on Adaptive Streams
NeurIPS 2022
Generative Models for Effective ML on Private, Decentralized Datasets
ICLR 2020
Learning Differentially Private Recurrent Language Models
ICLR 2018
A survey of Algorithms and Analysis for Adaptive Online Learning
JMLR 2017
Distributed Mean Estimation with Limited Communication
ICML 2017
Unconstrained Online Linear Learning in Hilbert Spaces: Minimax Algorithms and Normal Approximations
COLT 2014
Open Problem: Better Bounds for Online Logistic Regression
COLT 2012
Robust Submodular Observation Selection
JMLR 2008
Sleeping Experts and Bandits with Stochastic Action Availability and Adversarial Rewards
AISTATS 2005
A Fast Bundle-based Anytime Algorithm for Poker and other Convex Games
AISTATS 1999