Federated Learning

Privacy Amplification via Random Check-Ins NeurIPS 2020 Privacy-Preserving News Recommendation Model Learning EMNLP 2020 Quantized Compressive Sampling of Stochastic Gradients for Efficient Communication in Distributed Deep Learning AAAI 2020 Robust Federated Learning via Collaborative Machine Teaching AAAI 2020 Sol: Fast Distributed Computation Over Slow Networks NSDI 2020 Synthetic Data Generators -- Sequential and Private NeurIPS 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 Unsupervised Model Personalization While Preserving Privacy and Scalability: An Open Problem CVPR 2020 Agnostic Federated Learning ICML 2019 Collective Online Learning of Gaussian Processes in Massive Multi-Agent Systems AAAI 2019 Communication-Efficient Distributed Learning via Lazily Aggregated Quantized Gradients NeurIPS 2019 Differentially Private Distributed Data Summarization under Covariate Shift NeurIPS 2019 Embarrassingly Parallel Inference for Gaussian Processes JMLR 2019 Fall of Empires: Breaking Byzantine-tolerant SGD by Inner Product Manipulation UAI 2019 Multi-Agent Visualization for Explaining Federated Learning IJCAI 2019 Nonparametric Bayesian Aggregation for Massive Data JMLR 2019 Two-stage Federated Phenotyping and Patient Representation Learning ACL 2019 A Delay-tolerant Proximal-Gradient Algorithm for Distributed Learning ICML 2018 Communication Compression for Decentralized Training NeurIPS 2018 cpSGD: Communication-efficient and differentially-private distributed SGD NeurIPS 2018 Differentially Private Matrix Completion Revisited ICML 2018 Distributed Learning without Distress: Privacy-Preserving Empirical Risk Minimization NeurIPS 2018 Distributed Primal-Dual Optimization for Non-uniformly Distributed Data IJCAI 2018