federated learning

Adaptive Test-Time Personalization for Federated Learning NeurIPS 2023 A Data-Free Approach to Mitigate Catastrophic Forgetting in Federated Class Incremental Learning for Vision Tasks NeurIPS 2023 Addressing Budget Allocation and Revenue Allocation in Data Market Environments Using an Adaptive Sampling Algorithm ICML 2023 Adversarial Collaborative Learning on Non-IID Features ICML 2023 A Federated Approach for Hate Speech Detection EACL 2023 A Federated Learning Monitoring Tool for Self-Driving Car Simulation (Student Abstract) AAAI 2023 A First Look into the Carbon Footprint of Federated Learning JMLR 2023 A General Theory for Federated Optimization with Asynchronous and Heterogeneous Clients Updates JMLR 2023 Aggregating Capacity in FL through Successive Layer Training for Computationally-Constrained Devices NeurIPS 2023 Almost Cost-Free Communication in Federated Best Arm Identification AAAI 2023 Alternating Projected SGD for Equality-constrained Bilevel Optimization AISTATS 2023 (Amplified) Banded Matrix Factorization: A unified approach to private training NeurIPS 2023 Analysis of Error Feedback in Federated Non-Convex Optimization with Biased Compression: Fast Convergence and Partial Participation ICML 2023 Anchor Sampling for Federated Learning with Partial Client Participation ICML 2023 A Non-parametric View of FedAvg and FedProx:Beyond Stationary Points JMLR 2023 A Statistical Framework for Personalized Federated Learning and Estimation: Theory, Algorithms, and Privacy ICLR 2023 A Survey of Federated Evaluation in Federated Learning IJCAI 2023 Attacks against Federated Learning Defense Systems and their Mitigation JMLR 2023 Bayesian Federated Learning: A Survey IJCAI 2023 Bayesian Federated Neural Matching That Completes Full Information AAAI 2023 Better Generative Replay for Continual Federated Learning ICLR 2023 Beyond ADMM: A Unified Client-Variance-Reduced Adaptive Federated Learning Framework AAAI 2023 Bias-Eliminating Augmentation Learning for Debiased Federated Learning CVPR 2023 Bias Propagation in Federated Learning ICLR 2023 Bold but Cautious: Unlocking the Potential of Personalized Federated Learning through Cautiously Aggressive Collaboration ICCV 2023