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Federated Learning

1,360 papers

Papers per year

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Papers

Differentially Private and Communication Efficient Collaborative Learning AAAI 2021
On the Convergence of Communication-Efficient Local SGD for Federated Learning AAAI 2021
Personalized Cross-Silo Federated Learning on Non-IID Data AAAI 2021
FLAME: Differentially Private Federated Learning in the Shuffle Model AAAI 2021
Game of Gradients: Mitigating Irrelevant Clients in Federated Learning AAAI 2021
Defending against Backdoors in Federated Learning with Robust Learning Rate AAAI 2021
Federated Multi-Armed Bandits AAAI 2021
Federated Block Coordinate Descent Scheme for Learning Global and Personalized Models AAAI 2021
Toward Understanding the Influence of Individual Clients in Federated Learning AAAI 2021
Secure Bilevel Asynchronous Vertical Federated Learning with Backward Updating AAAI 2021
A Serverless Approach to Federated Learning Infrastructure Oriented for IoT/Edge Data Sources (Student Abstract) AAAI 2021
SecDD: Efficient and Secure Method for Remotely Training Neural Networks (Student Abstract) AAAI 2021
Collaborative Novelty Detection for Distributed Data by a Probabilistic Method ACML 2021
PFedAtt: Attention-based Personalized Federated Learning on Heterogeneous Clients ACML 2021
Regularized Mutual Learning for Personalized Federated Learning ACML 2021
CADA: Communication-Adaptive Distributed Adam AISTATS 2021
Revisiting Model-Agnostic Private Learning: Faster Rates and Active Learning AISTATS 2021
Mean-Variance Analysis in Bayesian Optimization under Uncertainty AISTATS 2021
Collaborative Classification from Noisy Labels AISTATS 2021
Free-rider Attacks on Model Aggregation in Federated Learning AISTATS 2021
Federated f-Differential Privacy AISTATS 2021
Optimal query complexity for private sequential learning against eavesdropping AISTATS 2021
Federated Learning with Compression: Unified Analysis and Sharp Guarantees AISTATS 2021
Shuffled Model of Differential Privacy in Federated Learning AISTATS 2021
Convergence and Accuracy Trade-Offs in Federated Learning and Meta-Learning AISTATS 2021