← Learning Paradigms
Machine Learning › Learning Paradigms ›

Federated Learning

551 directly classified papers

Papers per year

Papers

Federated Learning with Buffered Asynchronous Aggregation AISTATS 2022
Parallel MCMC Without Embarrassing Failures AISTATS 2022
Federated Reinforcement Learning with Environment Heterogeneity AISTATS 2022
Learning to Coordinate in Multi-Agent Systems: A Coordinated Actor-Critic Algorithm and Finite-Time Guarantees L4DC 2022
Rethinking Architecture Design for Tackling Data Heterogeneity in Federated Learning CVPR 2022
Layer-Wised Model Aggregation for Personalized Federated Learning CVPR 2022
Learning To Collaborate in Decentralized Learning of Personalized Models CVPR 2022
Learn From Others and Be Yourself in Heterogeneous Federated Learning CVPR 2022
Federated Class-Incremental Learning CVPR 2022
Escaping Data Scarcity for High-Resolution Heterogeneous Face Hallucination CVPR 2022
Communication-Constrained Distributed Quantile Regression with Optimal Statistical Guarantees JMLR 2022
In Differential Privacy, There is Truth: on Vote-Histogram Leakage in Ensemble Private Learning NIPS 2022
Distributed Learning of Finite Gaussian Mixtures JMLR 2022
FedScale: Benchmarking Model and System Performance of Federated Learning at Scale ICML 2022
Federated Learning with Positive and Unlabeled Data ICML 2022
Orchestra: Unsupervised Federated Learning via Globally Consistent Clustering ICML 2022
RSCFed: Random Sampling Consensus Federated Semi-Supervised Learning CVPR 2022
A Simple and Provably Efficient Algorithm for Asynchronous Federated Contextual Linear Bandits NIPS 2022
Fairness in Federated Learning via Core-Stability NIPS 2022
LAMP: Extracting Text from Gradients with Language Model Priors NIPS 2022
FedPop: A Bayesian Approach for Personalised Federated Learning NIPS 2022
pFL-Bench: A Comprehensive Benchmark for Personalized Federated Learning NIPS 2022
On Convergence of FedProx: Local Dissimilarity Invariant Bounds, Non-smoothness and Beyond NIPS 2022
GAL: Gradient Assisted Learning for Decentralized Multi-Organization Collaborations NIPS 2022
Muffliato: Peer-to-Peer Privacy Amplification for Decentralized Optimization and Averaging NIPS 2022