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Federated Learning

497 directly classified papers

Papers per year

Papers

FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout NIPS 2021
CANITA: Faster Rates for Distributed Convex Optimization with Communication Compression NIPS 2021
Leveraging Spatial and Temporal Correlations in Sparsified Mean Estimation NIPS 2021
Linear Convergence in Federated Learning: Tackling Client Heterogeneity and Sparse Gradients NIPS 2021
Differentially Private Learning with Adaptive Clipping NIPS 2021
Moshpit SGD: Communication-Efficient Decentralized Training on Heterogeneous Unreliable Devices NIPS 2021
Federated Graph Classification over Non-IID Graphs NIPS 2021
On Large-Cohort Training for Federated Learning NIPS 2021
DeepReduce: A Sparse-tensor Communication Framework for Federated Deep Learning NIPS 2021
Collaborative Learning in the Jungle (Decentralized, Byzantine, Heterogeneous, Asynchronous and Nonconvex Learning) NIPS 2021
Federated Linear Contextual Bandits NIPS 2021
CRFL: Certifiably Robust Federated Learning against Backdoor Attacks ICML 2021
Federated Model Distillation with Noise-Free Differential Privacy IJCAI 2021
Hiding Numerical Vectors in Local Private and Shuffled Messages IJCAI 2021
TextHide: Tackling Data Privacy in Language Understanding Tasks EMNLP 2020
Privacy Amplification via Random Check-Ins NIPS 2020
Minibatch vs Local SGD for Heterogeneous Distributed Learning NIPS 2020
Synthetic Data Generators -- Sequential and Private NIPS 2020
A Scalable Approach for Privacy-Preserving Collaborative Machine Learning NIPS 2020
GS-WGAN: A Gradient-Sanitized Approach for Learning Differentially Private Generators NIPS 2020
Attack of the Tails: Yes, You Really Can Backdoor Federated Learning NIPS 2020
Inverting Gradients - How easy is it to break privacy in federated learning? NIPS 2020
Orchard: Differentially Private Analytics at Scale OSDI 2020
Quantized Compressive Sampling of Stochastic Gradients for Efficient Communication in Distributed Deep Learning AAAI 2020
FetchSGD: Communication-Efficient Federated Learning with Sketching ICML 2020