Paul Mangold
9 papers · 2022–2025 · 3 conferences · across top CS/AI conferences
Achievements
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🐣 Hot Topic Early Bird 🧭 Keyword Pioneer 🌍 Conference Polyglot (3) 🌉 Interdisciplinary Bridge 🐝 Cross-Pollinator (10)
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Renaissance Researcher
(5)
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Taxonomy Completionist
(18)
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Mega-Team
(24)
Conferences
AISTATS (4)
ICML (3)
NIPS (2)
Top co-authors
Research topics
Keywords
differential privacy
(3)
empirical risk minimization
(2)
stochastic gradient descent
(1)
temporal difference learning
(1)
coordinate descent
(1)
sensitivity analysis
(1)
greedy coordinate descent
(1)
high-dimensional optimization
(1)
lipschitz continuity
(1)
optimization algorithm
(1)
benchmark dataset
(1)
gradient clipping
(1)
group fairness
(1)
control variate
(1)
gaussian mechanism
(1)
cross-silo federated learning
(1)
privacy accounting
(1)
quasi-sparse solution
(1)
non-asymptotic bound
(1)
private gradient descent
(1)
Papers
Scaffold with Stochastic Gradients: New Analysis with Linear Speed-Up
ICML 2025
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
The Relative Gaussian Mechanism and its Application to Private Gradient Descent
AISTATS 2024
SCAFFLSA: Taming Heterogeneity in Federated Linear Stochastic Approximation and TD Learning
NIPS 2024
Differential Privacy has Bounded Impact on Fairness in Classification
ICML 2023
High-Dimensional Private Empirical Risk Minimization by Greedy Coordinate Descent
AISTATS 2023
FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings
NIPS 2022
Differentially Private Coordinate Descent for Composite Empirical Risk Minimization
ICML 2022