Federated Learning

Truthful Data Acquisition via Peer Prediction NeurIPS 2020 Adaptive Gradient-Based Meta-Learning Methods NeurIPS 2019 A Little Is Enough: Circumventing Defenses For Distributed Learning NeurIPS 2019 Analyzing Federated Learning through an Adversarial Lens ICML 2019 Collective Online Learning of Gaussian Processes in Massive Multi-Agent Systems AAAI 2019 Communication-Efficient Distributed Blockwise Momentum SGD with Error-Feedback NeurIPS 2019 Communication-Efficient Distributed Learning via Lazily Aggregated Quantized Gradients NeurIPS 2019 Data Poisoning Attacks on Stochastic Bandits ICML 2019 Defending Against Saddle Point Attack in Byzantine-Robust Distributed Learning ICML 2019 Differentially Private Distributed Data Summarization under Covariate Shift NeurIPS 2019 Efficient Protocol for Collaborative Dictionary Learning in Decentralized Networks IJCAI 2019 Guided Meta-Policy Search NeurIPS 2019 Language Discrimination and Transfer Learning for Similar Languages: Experiments with Feature Combinations and Adaptation NAACL 2019 Learning Auctions with Robust Incentive Guarantees NeurIPS 2019 Multi-scale Online Learning: Theory and Applications to Online Auctions and Pricing JMLR 2019 Optimal Statistical Rates for Decentralised Non-Parametric Regression with Linear Speed-Up NeurIPS 2019 RSA: Byzantine-Robust Stochastic Aggregation Methods for Distributed Learning from Heterogeneous Datasets AAAI 2019 Semi-Cyclic Stochastic Gradient Descent ICML 2019 Sketching for Latent Dirichlet-Categorical Models AISTATS 2019 Sublinear Space Private Algorithms Under the Sliding Window Model ICML 2019 Universal Multi-Party Poisoning Attacks ICML 2019 COLA: Decentralized Linear Learning NeurIPS 2018 Communication Compression for Decentralized Training NeurIPS 2018 Contamination Attacks and Mitigation in Multi-Party Machine Learning NeurIPS 2018 Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training ICLR 2018