Paul Mangold
10 papers · 2022–2026 · 4 venues · across top CS/AI venues
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Achievements
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🐣 Hot Topic Early Bird 🌍 Conference Polyglot · Bronze 🌉 Interdisciplinary Bridge · Silver 🗺️ Taxonomy Completionist (23) 👥 Mega-Team · Squad
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Keyword Collector
(52)
💎
Century Club · Bronze
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Unstoppable · Bronze
Venues
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Research topics
Machine Learning
(10)
Optimization & Theory
(8)
Application Areas
(6)
Mathematics & Optimization
(4)
Security & Privacy
(4)
Differential Privacy
(4)
Artificial Intelligence
(2)
Core AI
(2)
Core Methods
(2)
Learning Paradigms · Artificial Intelligence
(2)
Learning Paradigms · Machine Learning
(2)
Optimization
(2)
Deep Learning
(1)
Reinforcement Learning
(1)
Applications
(1)
Keywords
differential privacy
(3)
linear speedup
(2)
empirical risk minimization
(2)
federated learning
(2)
coordinate descent
(1)
temporal difference learning
(1)
stochastic gradient descent
(1)
regret minimization
(1)
stochastic gradient
(1)
value iteration
(1)
high-dimensional optimization
(1)
gaussian approximation
(1)
sensitivity analysis
(1)
markov chain
(1)
greedy coordinate descent
(1)
stochastic approximation
(1)
communication complexity
(1)
stationary distribution
(1)
lipschitz continuity
(1)
wasserstein distance
(1)
Papers
Gaussian Approximation and Multiplier Bootstrap for Federated Linear Stochastic Approximation
UAI 2026
Federated UCBVI: Communication-Efficient Federated Regret Minimization with Heterogeneous Agents
AISTATS 2025
Refined Analysis of Constant Step Size Federated Averaging and Federated Richardson-Romberg Extrapolation
AISTATS 2025
Scaffold with Stochastic Gradients: New Analysis with Linear Speed-Up
ICML 2025
SCAFFLSA: Taming Heterogeneity in Federated Linear Stochastic Approximation and TD Learning
NeurIPS 2024
The Relative Gaussian Mechanism and its Application to Private Gradient Descent
AISTATS 2024
Differential Privacy has Bounded Impact on Fairness in Classification
ICML 2023
High-Dimensional Private Empirical Risk Minimization by Greedy Coordinate Descent
AISTATS 2023
Differentially Private Coordinate Descent for Composite Empirical Risk Minimization
ICML 2022
FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings
NeurIPS 2022