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07/12/2022
Federated Unlearning: How to Efficiently Erase a Client in FL?
With privacy legislation empowering users with the right to be forgotten...
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04/16/2022
A Distributed and Elastic Aggregation Service for Scalable Federated Learning Systems
Federated Learning has promised a new approach to resolve the challenges...
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02/25/2022
Towards an Accountable and Reproducible Federated Learning: A FactSheets Approach
Federated Learning (FL) is a novel paradigm for the shared training of m...
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02/16/2022
Single-shot Hyper-parameter Optimization for Federated Learning: A General Algorithm Analysis
We address the relatively unexplored problem of hyper-parameter optimiza...
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12/15/2021
FLoRA: Single-shot Hyper-parameter Optimization for Federated Learning
We address the relatively unexplored problem of hyper-parameter optimiza...
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08/10/2021
Privacy-Preserving Machine Learning: Methods, Challenges and Directions
Machine learning (ML) is increasingly being adopted in a wide variety of...
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07/26/2021
LEGATO: A LayerwisE Gradient AggregaTiOn Algorithm for Mitigating Byzantine Attacks in Federated Learning
Federated learning has arisen as a mechanism to allow multiple participa...
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03/05/2021
FedV: Privacy-Preserving Federated Learning over Vertically Partitioned Data
Federated learning (FL) has been proposed to allow collaborative trainin...
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02/01/2021
Curse or Redemption? How Data Heterogeneity Affects the Robustness of Federated Learning
Data heterogeneity has been identified as one of the key features in fed...
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12/11/2020
Adaptive Histogram-Based Gradient Boosted Trees for Federated Learning
Federated Learning (FL) is an approach to collaboratively train a model ...
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12/04/2020
Mitigating Bias in Federated Learning
As methods to create discrimination-aware models develop, they focus on ...
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07/22/2020
IBM Federated Learning: an Enterprise Framework White Paper V0.1
Federated Learning (FL) is an approach to conduct machine learning witho...
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01/25/2020
TiFL: A Tier-based Federated Learning System
Federated Learning (FL) enables learning a shared model across many clie...
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12/12/2019
HybridAlpha: An Efficient Approach for Privacy-Preserving Federated Learning
Federated learning has emerged as a promising approach for collaborative...
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12/07/2018
A Hybrid Approach to Privacy-Preserving Federated Learning
Training machine learning models often requires data from multiple parti...
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11/09/2018
