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Federated Learning

497 directly classified papers

Papers per year

Papers

Active Membership Inference Attack under Local Differential Privacy in Federated Learning AISTATS 2023
Distributed Offline Policy Optimization Over Batch Data AISTATS 2023
The communication cost of security and privacy in federated frequency estimation AISTATS 2023
Fixing by Mixing: A Recipe for Optimal Byzantine ML under Heterogeneity AISTATS 2023
Catalyst Acceleration of Error Compensated Methods Leads to Better Communication Complexity AISTATS 2023
Doubly Adversarial Federated Bandits ICML 2023
Bayesian Federated Learning: A Survey IJCAI 2023
Conformal Prediction for Federated Uncertainty Quantification Under Label Shift ICML 2023
Federated Incremental Semantic Segmentation CVPR 2023
HyperFed: Hyperbolic Prototypes Exploration with Consistent Aggregation for Non-IID Data in Federated Learning IJCAI 2023
DIFF2: Differential Private Optimization via Gradient Differences for Nonconvex Distributed Learning ICML 2023
Algorithms for bounding contribution for histogram estimation under user-level privacy ICML 2023
Byzantine-Robust Learning on Heterogeneous Data via Gradient Splitting ICML 2023
Globally Consistent Federated Graph Autoencoder for Non-IID Graphs IJCAI 2023
FedPass: Privacy-Preserving Vertical Federated Deep Learning with Adaptive Obfuscation IJCAI 2023
Revisiting Weighted Aggregation in Federated Learning with Neural Networks ICML 2023
FedDisco: Federated Learning with Discrepancy-Aware Collaboration ICML 2023
Personalized Federated Learning with Inferred Collaboration Graphs ICML 2023
Towards Attack-tolerant Federated Learning via Critical Parameter Analysis ICCV 2023
Analysis of Error Feedback in Federated Non-Convex Optimization with Biased Compression: Fast Convergence and Partial Participation ICML 2023
Adversarial Collaborative Learning on Non-IID Features ICML 2023
Cocktail Party Attack: Breaking Aggregation-Based Privacy in Federated Learning Using Independent Component Analysis ICML 2023
Out-of-Distribution Generalization of Federated Learning via Implicit Invariant Relationships ICML 2023
Privacy-Aware Compression for Federated Learning Through Numerical Mechanism Design ICML 2023
User-level Private Stochastic Convex Optimization with Optimal Rates ICML 2023