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Federated Learning

1,360 papers

Papers per year

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4
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Papers

KungFu: Making Training in Distributed Machine Learning Adaptive OSDI 2020
Active Preference-Based Gaussian Process Regression for Reward Learning RSS 2020
99% of Worker-Master Communication in Distributed Optimization Is Not Needed UAI 2020
Differentially Private Distributed Data Summarization under Covariate Shift NIPS 2019
Communication-Efficient Distributed Learning via Lazily Aggregated Quantized Gradients NIPS 2019
Communication-Efficient Distributed Blockwise Momentum SGD with Error-Feedback NIPS 2019
Learning Auctions with Robust Incentive Guarantees NIPS 2019
Guided Meta-Policy Search NIPS 2019
Optimal Statistical Rates for Decentralised Non-Parametric Regression with Linear Speed-Up NIPS 2019
A Little Is Enough: Circumventing Defenses For Distributed Learning NIPS 2019
Adaptive Gradient-Based Meta-Learning Methods NIPS 2019
RSA: Byzantine-Robust Stochastic Aggregation Methods for Distributed Learning from Heterogeneous Datasets AAAI 2019
Collective Online Learning of Gaussian Processes in Massive Multi-Agent Systems AAAI 2019
Sketching for Latent Dirichlet-Categorical Models AISTATS 2019
Analyzing Federated Learning through an Adversarial Lens ICML 2019
Semi-Cyclic Stochastic Gradient Descent ICML 2019
Data Poisoning Attacks on Stochastic Bandits ICML 2019
Universal Multi-Party Poisoning Attacks ICML 2019
Sublinear Space Private Algorithms Under the Sliding Window Model ICML 2019
Defending Against Saddle Point Attack in Byzantine-Robust Distributed Learning ICML 2019
Efficient Protocol for Collaborative Dictionary Learning in Decentralized Networks IJCAI 2019
Multi-scale Online Learning: Theory and Applications to Online Auctions and Pricing JMLR 2019
Language Discrimination and Transfer Learning for Similar Languages: Experiments with Feature Combinations and Adaptation NAACL 2019
COLA: Decentralized Linear Learning NIPS 2018
Contamination Attacks and Mitigation in Multi-Party Machine Learning NIPS 2018