Marco Lorenzi
10 papers · 2018–2025 · 5 conferences · across top CS/AI conferences
Achievements
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π£ Hot Topic Early Bird π Interdisciplinary Bridge πΊοΈ Taxonomy Completionist (11) π§ Keyword Pioneer π Conference Polyglot (5)
π£
Hot Topic Early Bird
π
Interdisciplinary Bridge
π₯
Mega-Team
(24)
π
Century Club
(10)
π
Conference Pioneer
β
The Questioner
π₯
Unstoppable
(5)
Conferences
ICML (4)
AISTATS (2)
JMLR (2)
MICCAI (1)
NIPS (1)
Top co-authors
Research topics
Keywords
federated learning
(3)
heterogeneous datum
(2)
model aggregation
(2)
adversarial learning
(1)
non-convex optimization
(1)
uncertainty quantification
(1)
medical imaging
(1)
convergence analysis
(1)
gradient aggregation
(1)
distributed learning
(1)
privacy preservation
(1)
machine unlearning
(1)
variance reduction
(1)
asynchronous optimization
(1)
monotonic regression
(1)
stochastic variational inference
(1)
latent representation
(1)
marginal distribution
(1)
benchmark dataset
(1)
variational autoencoder
(1)
Papers
When to Forget? Complexity Trade-offs in Machine Unlearning
ICML 2025
Federated Multi-Centric Image Segmentation with Uneven Label Distribution
MICCAI 2024
SIFU: Sequential Informed Federated Unlearning for Efficient and Provable Client Unlearning in Federated Optimization
AISTATS 2024
On Tail Decay Rate Estimation of Loss Function Distributions
JMLR 2024
A General Theory for Federated Optimization with Asynchronous and Heterogeneous Clients Updates
JMLR 2023
FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings
NIPS 2022
Clustered Sampling: Low-Variance and Improved Representativity for Clients Selection in Federated Learning
ICML 2021
Free-rider Attacks on Model Aggregation in Federated Learning
AISTATS 2021
Sparse Multi-Channel Variational Autoencoder for the Joint Analysis of Heterogeneous Data
ICML 2019
Constraining the Dynamics of Deep Probabilistic Models
ICML 2018