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Federated Learning

497 directly classified papers

Papers per year

Papers

Moniqua: Modulo Quantized Communication in Decentralized SGD ICML 2020
InstaHide: Instance-hiding Schemes for Private Distributed Learning ICML 2020
FedED: Federated Learning via Ensemble Distillation for Medical Relation Extraction EMNLP 2020
Synthetic Learning: Learn From Distributed Asynchronized Discriminator GAN Without Sharing Medical Image Data CVPR 2020
Fall of Empires: Breaking Byzantine-tolerant SGD by Inner Product Manipulation UAI 2019
Multi-Agent Visualization for Explaining Federated Learning IJCAI 2019
Differentially Private Distributed Data Summarization under Covariate Shift NIPS 2019
Communication-Efficient Distributed Learning via Lazily Aggregated Quantized Gradients NIPS 2019
Distributed Self-Paced Learning in Alternating Direction Method of Multipliers IJCAI 2018
cpSGD: Communication-efficient and differentially-private distributed SGD NIPS 2018
Communication Compression for Decentralized Training NIPS 2018
Distributed Learning without Distress: Privacy-Preserving Empirical Risk Minimization NIPS 2018
Differentially Private Matrix Completion Revisited ICML 2018
A Delay-tolerant Proximal-Gradient Algorithm for Distributed Learning ICML 2018
The Hidden Vulnerability of Distributed Learning in Byzantium ICML 2018
Crowd Learning: Improving Online Decision Making Using Crowdsourced Data IJCAI 2017
Bootstrap Model Aggregation for Distributed Statistical Learning NIPS 2016
Distributed Estimation, Information Loss and Exponential Families NIPS 2014
Distributed Learning, Communication Complexity and Privacy COLT 2012
Distributed Probabilistic Learning for Camera Networks with Missing Data NIPS 2012
Multiparty Differential Privacy via Aggregation of Locally Trained Classifiers NIPS 2010
Asynchronous Distributed Learning of Topic Models NIPS 2008