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Federated Learning

1355 directly classified papers

Papers per year

Papers

Collaborative Machine Learning with Incentive-Aware Model Rewards ICML 2020
A Federated Approach in Training Acoustic Models INTERSPEECH 2020
Private Protocols for U-Statistics in the Local Model and Beyond AISTATS 2020
Breaking the Communication-Privacy-Accuracy Trilemma NIPS 2020
Personalized Federated Learning with Theoretical Guarantees: A Model-Agnostic Meta-Learning Approach NIPS 2020
Privacy Amplification via Random Check-Ins NIPS 2020
Minibatch vs Local SGD for Heterogeneous Distributed Learning NIPS 2020
Federated Principal Component Analysis NIPS 2020
FedSplit: an algorithmic framework for fast federated optimization NIPS 2020
Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization NIPS 2020
Election Coding for Distributed Learning: Protecting SignSGD against Byzantine Attacks NIPS 2020
Distributionally Robust Federated Averaging NIPS 2020
Truthful Data Acquisition via Peer Prediction NIPS 2020
Throughput-Optimal Topology Design for Cross-Silo Federated Learning NIPS 2020
An Efficient Framework for Clustered Federated Learning NIPS 2020
Learning discrete distributions: user vs item-level privacy NIPS 2020
Second Order Optimality in Decentralized Non-Convex Optimization via Perturbed Gradient Tracking NIPS 2020
Training Keyword Spotting Models on Non-IID Data with Federated Learning INTERSPEECH 2020
Federated Learning for Spoken Language Understanding COLING 2020
FedBoost: A Communication-Efficient Algorithm for Federated Learning ICML 2020
A Unified Theory of Decentralized SGD with Changing Topology and Local Updates ICML 2020
Acceleration for Compressed Gradient Descent in Distributed and Federated Optimization ICML 2020
How to Solve Fair k-Center in Massive Data Models ICML 2020
Distributed, partially collapsed MCMC for Bayesian Nonparametrics AISTATS 2020
FedED: Federated Learning via Ensemble Distillation for Medical Relation Extraction EMNLP 2020