CCF A类会议或期刊----近两年联邦学习相关论文

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会议/期刊 论文
neurips2020 Lower Bounds and Optimal Algorithms for Personalized Federated Learning.
neurips2020 Ensemble Distillation for Robust Model Fusion in Federated Learning.
neurips2020 Personalized Federated Learning with Theoretical Guarantees: A Model-Agnostic Meta-Learning Approach.
neurips2020 Group Knowledge Transfer: Federated Learning of Large CNNs at the Edge.
neurips2020 Attack of the Tails: Yes, You Really Can Backdoor Federated Learning.
neurips2020 Inverting Gradients - How easy is it to break privacy in federated learning?
neurips2020 Throughput-Optimal Topology Design for Cross-Silo Federated Learning.
neurips2020 An Efficient Framework for Clustered Federated Learning.
neurips2020 Personalized Federated Learning with Moreau Envelopes.
neurips2020 Robust Federated Learning: The Case of Affine Distribution Shifts.
kdd2021 FedRS: Federated Learning with Restricted Softmax for Label Distribution Non-IID Data.
kdd2021 Fed2: Feature-Aligned Federated Learning.
kdd2021 FLOP: Federated Learning on Medical Datasets using Partial Networks.
kdd2021 AsySQN: Faster Vertical Federated Learning Algorithms with Better Computation Resource Utilization.
kdd2021 Towards Fair Federated Learning.
ICDE2021 Feature Inference Attack on Model Predictions in Vertical Federated Learning.
ICDE2021 An Efficient Approach for Cross-Silo Federated Learning to Rank.
ACMMM2020 InvisibleFL: Federated Learning over Non-Informative Intermediate Updates against Multimedia Privacy Leakages.
AAAI2021 Model-sharing Games: Analyzing Federated Learning Under Voluntary Participation.
AAAI2021 Provably Secure Federated Learning against Malicious Clients.
AAAI2021 On the Convergence of Communication-Efficient Local SGD for Federated Learning.
AAAI2021 Personalized Cross-Silo Federated Learning on Non-IID Data.
AAAI2021 FLAME: Differentially Private Federated Learning in the Shuffle Model.
AAAI2021 Game of Gradients: Mitigating Irrelevant Clients in Federated Learning.
AAAI2021 Defending against Backdoors in Federated Learning with Robust Learning Rate.
AAAI2021 Addressing Class Imbalance in Federated Learning.
AAAI2021 Toward Understanding the Influence of Individual Clients in Federated Learning.
AAAI2021 Curse or Redemption? How Data Heterogeneity Affects the Robustness of Federated Learning.
AAAI2021 Secure Bilevel Asynchronous Vertical Federated Learning with Backward Updating.
AAAI2021 A Serverless Approach to Federated Learning Infrastructure Oriented for IoT/Edge Data Sources (Student Abstract).
AAAI2020 Robust Federated Learning via Collaborative Machine Teaching.
AAAI2020 Federated Learning for Vision-and-Language Grounding Problems.
AAAI2020 FedVision: An Online Visual Object Detection Platform Powered by Federated Learning.
WWW2021 Characterizing Impacts of Heterogeneity in Federated Learning upon Large-Scale Smartphone Data.
WWW2021 Incentive Mechanism for Horizontal Federated Learning Based on Reputation and Reverse Auction.
WWW2021 Hierarchical Personalized Federated Learning for User Modeling.
ICML2021 Federated Learning under Arbitrary Communication Patterns.
ICML2021 One for One, or All for All: Equilibria and Optimality of Collaboration in Federated Learning.
ICML2021 Exploiting Shared Representations for Personalized Federated Learning.
ICML2021 Clustered Sampling: Low-Variance and Improved Representativity for Clients Selection in Federated Learning.
ICML2021 Federated Learning of User Verification Models Without Sharing Embeddings.
ICML2021 FL-NTK: A Neural Tangent Kernel-based Framework for Federated Learning Analysis.
ICML2021 The Distributed Discrete Gaussian Mechanism for Federated Learning with Secure Aggregation.
ICML2021 Gradient Disaggregation: Breaking Privacy in Federated Learning by Reconstructing the User Participant Matrix.
ICML2021 Ditto: Fair and Robust Federated Learning Through Personalization.
ICML2021 Bias-Variance Reduced Local SGD for Less Heterogeneous Federated Learning.
ICML2021 Personalized Federated Learning using Hypernetworks.
ICML2021 CRFL: Certifiably Robust Federated Learning against Backdoor Attacks.
ICML2021 Data-Free Knowledge Distillation for Heterogeneous Federated Learning.
ICML2020 FedBoost: A Communication-Efficient Algorithm for Federated Learning.
ICML2020 SCAFFOLD: Stochastic Controlled Averaging for Federated Learning.
ICML2020 From Local SGD to Local Fixed-Point Methods for Federated Learning.
ICML2020 FetchSGD: Communication-Efficient Federated Learning with Sketching.
ICML2020 Federated Learning with Only Positive Labels.
ICML2019 Analyzing Federated Learning through an Adversarial Lens.
ICML2019 Agnostic Federated Learning.
ICML2019 Bayesian Nonparametric Federated Learning of Neural Networks.
CVPR2021 Multi-Institutional Collaborations for Improving Deep Learning-Based Magnetic Resonance Image Reconstruction Using Federated Learning.
CVPR2021 Soteria: Provable Defense Against Privacy Leakage in Federated Learning From Representation Perspective.
CVPR2021 Model-Contrastive Federated Learning.
CVPRW2021 Are All Users Treated Fairly in Federated Learning Systems?
CVPRW2021 Cluster-Driven Graph Federated Learning Over Multiple Domains.
CVPRW2021 Towards Fair Federated Learning With Zero-Shot Data Augmentation.
ICCV2021 FedAffect: Few-shot federated learning for facial expression recognition.
IJCAI2021 H-FL: A Hierarchical Communication-Efficient and Privacy-Protected Architecture for Federated Learning.
IJCAI2021 Federated Learning with Sparsification-Amplified Privacy and Adaptive Optimization.
IJCAI2021 Practical One-Shot Federated Learning for Cross-Silo Setting.
IJCAI2021 LDP-FL: Practical Private Aggregation in Federated Learning with Local Differential Privacy.
IJCAI2021 Federated Learning with Fair Averaging.
IJCAI2021 Behavior Mimics Distribution: Combining Individual and Group Behaviors for Federated Learning.
IJCAI2020 A Multi-player Game for Studying Federated Learning Incentive Schemes.
TPAMI2022 Lazily Aggregated Quantized Gradient Innovation for Communication-Efficient Federated Learning.
JMLR2021 One-Shot Federated Learning: Theoretical Limits and Algorithms to Achieve Them.