federated learning

Is Local SGD Better than Minibatch SGD? ICML 2020 Learning discrete distributions: user vs item-level privacy NeurIPS 2020 Lower Bounds and Optimal Algorithms for Personalized Federated Learning NeurIPS 2020 Minibatch vs Local SGD for Heterogeneous Distributed Learning NeurIPS 2020 Model Fusion with Kullback-Leibler Divergence ICML 2020 On the Convergence of FedAvg on Non-IID Data ICLR 2020 Personalized Federated Learning with Moreau Envelopes NeurIPS 2020 Personalized Federated Learning with Theoretical Guarantees: A Model-Agnostic Meta-Learning Approach NeurIPS 2020 Practical Federated Gradient Boosting Decision Trees AAAI 2020 Privacy Amplification via Random Check-Ins NeurIPS 2020 Privacy-Preserving News Recommendation Model Learning EMNLP 2020 Robust Federated Learning: The Case of Affine Distribution Shifts NeurIPS 2020 Robust Federated Learning via Collaborative Machine Teaching AAAI 2020 SCAFFOLD: Stochastic Controlled Averaging for Federated Learning ICML 2020 Sequence-Level Self-Learning with Multiple Hypotheses Interspeech 2020 Synthetic Learning: Learn From Distributed Asynchronized Discriminator GAN Without Sharing Medical Image Data CVPR 2020 Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization NeurIPS 2020 TextHide: Tackling Data Privacy in Language Understanding Tasks EMNLP 2020 Throughput-Optimal Topology Design for Cross-Silo Federated Learning NeurIPS 2020 Towards Crowdsourced Training of Large Neural Networks using Decentralized Mixture-of-Experts NeurIPS 2020 Training Keyword Spotting Models on Non-IID Data with Federated Learning Interspeech 2020 Adaptive Gradient-Based Meta-Learning Methods NeurIPS 2019 Agnostic Federated Learning ICML 2019 A Little Is Enough: Circumventing Defenses For Distributed Learning NeurIPS 2019 Analyzing Federated Learning through an Adversarial Lens ICML 2019