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07/02/2023
FedDefender: Backdoor Attack Defense in Federated Learning
Federated Learning (FL) is a privacy-preserving distributed machine lear...
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05/26/2023
A Framework for Incentivized Collaborative Learning
Collaborations among various entities, such as companies, research labs,...
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05/03/2023
Attention Based Feature Fusion For Multi-Agent Collaborative Perception
In the domain of intelligent transportation systems (ITS), collaborative...
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04/15/2023
PI-FL: Personalized and Incentivized Federated Learning
Personalized FL has been widely used to cater to heterogeneity challenge...
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04/14/2023
The Second Monocular Depth Estimation Challenge
This paper discusses the results for the second edition of the Monocular...
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01/09/2023
FedDebug: Systematic Debugging for Federated Learning Applications
In Federated Learning (FL), clients train a model locally and share it w...
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12/17/2022
Personalized Federated Recommender Systems with Private and Partially Federated AutoEncoders
Recommender Systems (RSs) have become increasingly important in many app...
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09/03/2022
Sion: Elastic Serverless Cloud Storage
Cloud object storage such as AWS S3 is cost-effective and highly elastic...
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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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11/29/2021
SPATL: Salient Parameter Aggregation and Transfer Learning for Heterogeneous Clients in Federated Learning
Efficient federated learning is one of the key challenges for training a...
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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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06/13/2021
Adaptive Dynamic Pruning for Non-IID Federated Learning
Federated Learning (FL) has emerged as a new paradigm of training machin...
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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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10/14/2020
Wukong: A Scalable and Locality-Enhanced Framework for Serverless Parallel Computing
Serverless computing is increasingly being used for parallel computing, ...
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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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01/28/2020
InfiniCache: Exploiting Ephemeral Serverless Functions to Build a Cost-Effective Memory Cache
Internet-scale web applications are becoming increasingly storage-intens...
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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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09/19/2019
Towards Federated Graph Learning for Collaborative Financial Crimes Detection
Financial crime is a large and growing problem, in some way touching alm...
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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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08/08/2018
