Advances and Open Problems in Federated Learning

Citation edge evidence

Each row is directed from the citing work to the cited work. Source status remains readable without the interactive graph.

• Text Data Augmentation for Deep Learning→Advances and Open Problems in Federated LearningLegacy edge — source detail unavailable
• Advances and Open Problems in Federated Learning→A Survey on Transfer LearningLegacy edge — source detail unavailable
• Advances and Open Problems in Federated Learning→Adaptive Subgradient Methods for Online Learning and Stochastic OptimizationLegacy edge — source detail unavailable
• Advances and Open Problems in Federated Learning→Calibrating Noise to Sensitivity in Private Data AnalysisLegacy edge — source detail unavailable
• Advances and Open Problems in Federated Learning→Fully homomorphic encryption using ideal latticesLegacy edge — source detail unavailable
• Advances and Open Problems in Federated Learning→Federated Machine LearningLegacy edge — source detail unavailable
• Advances and Open Problems in Federated Learning→Deep Learning with Differential PrivacyLegacy edge — source detail unavailable
• Advances and Open Problems in Federated Learning→The Byzantine Generals ProblemLegacy edge — source detail unavailable
• Advances and Open Problems in Federated Learning→Model-Agnostic Meta-Learning for Fast Adaptation of Deep NetworksLegacy edge — source detail unavailable
• Advances and Open Problems in Federated Learning→Intriguing properties of neural networksLegacy edge — source detail unavailable
• Advances and Open Problems in Federated Learning→Prototypical Networks for Few-shot LearningLegacy edge — source detail unavailable
• Advances and Open Problems in Federated Learning→Communication-Efficient Learning of Deep Networks from Decentralized DataLegacy edge — source detail unavailable
• Advances and Open Problems in Federated Learning→Membership Inference Attacks Against Machine Learning ModelsLegacy edge — source detail unavailable
• Advances and Open Problems in Federated Learning→The Sybil AttackLegacy edge — source detail unavailable
• Advances and Open Problems in Federated Learning→Untraceable electronic mail, return addresses, and digital pseudonymsLegacy edge — source detail unavailable
• Advances and Open Problems in Federated Learning→Tor: The Second-Generation Onion RouterLegacy edge — source detail unavailable
• Advances and Open Problems in Federated Learning→The Algorithmic Foundations of Differential PrivacyLegacy edge — source detail unavailable
• Advances and Open Problems in Federated Learning→Practical Secure Aggregation for Privacy-Preserving Machine LearningLegacy edge — source detail unavailable
• Advances and Open Problems in Federated Learning→A theory of learning from different domainsLegacy edge — source detail unavailable
• Advances and Open Problems in Federated Learning→Practical Black-Box Attacks against Machine LearningLegacy edge — source detail unavailable
• Advances and Open Problems in Federated Learning→Fairness through awarenessLegacy edge — source detail unavailable
• Advances and Open Problems in Federated Learning→Differential Privacy: A Survey of ResultsLegacy edge — source detail unavailable
• Advances and Open Problems in Federated Learning→The Knowledge Complexity of Interactive Proof SystemsLegacy edge — source detail unavailable
• Advances and Open Problems in Federated Learning→Algorithms for Hyper-Parameter OptimizationLegacy edge — source detail unavailable
• Advances and Open Problems in Federated Learning→Federated Learning: Strategies for Improving Communication EfficiencyLegacy edge — source detail unavailable
• Advances and Open Problems in Federated Learning→Privacy-preserving data miningLegacy edge — source detail unavailable
• Advances and Open Problems in Federated Learning→Model Inversion Attacks that Exploit Confidence Information and Basic CountermeasuresLegacy edge — source detail unavailable
• Advances and Open Problems in Federated Learning→Protocols for secure computationsLegacy edge — source detail unavailable
• Advances and Open Problems in Federated Learning→Optimization as a Model for Few-Shot LearningLegacy edge — source detail unavailable
• Advances and Open Problems in Federated Learning→SecureML: A System for Scalable Privacy-Preserving Machine LearningLegacy edge — source detail unavailable
• Advances and Open Problems in Federated Learning→Ensemble Adversarial Training: Attacks and DefensesLegacy edge — source detail unavailable
• Advances and Open Problems in Federated Learning→Our Data, Ourselves: Privacy Via Distributed Noise GenerationLegacy edge — source detail unavailable
• Advances and Open Problems in Federated Learning→(Leveled) fully homomorphic encryption without bootstrappingLegacy edge — source detail unavailable
• Advances and Open Problems in Federated Learning→Private information retrievalLegacy edge — source detail unavailable
• Advances and Open Problems in Federated Learning→Towards Deep Learning Models Resistant to Adversarial AttacksLegacy edge — source detail unavailable
• Advances and Open Problems in Federated Learning→Neural Cleanse: Identifying and Mitigating Backdoor Attacks in Neural NetworksLegacy edge — source detail unavailable
• The Sybil Attack→Untraceable electronic mail, return addresses, and digital pseudonymsLegacy edge — source detail unavailable
• The Sybil Attack→The Byzantine Generals ProblemLegacy edge — source detail unavailable
• Our Data, Ourselves: Privacy Via Distributed Noise Generation→Calibrating Noise to Sensitivity in Private Data AnalysisLegacy edge — source detail unavailable
• Our Data, Ourselves: Privacy Via Distributed Noise Generation→Protocols for secure computationsLegacy edge — source detail unavailable
• Our Data, Ourselves: Privacy Via Distributed Noise Generation→Privacy-preserving data miningLegacy edge — source detail unavailable
• Our Data, Ourselves: Privacy Via Distributed Noise Generation→The Byzantine Generals ProblemLegacy edge — source detail unavailable
• Tor: The Second-Generation Onion Router→The Sybil AttackLegacy edge — source detail unavailable
• Tor: The Second-Generation Onion Router→Untraceable electronic mail, return addresses, and digital pseudonymsLegacy edge — source detail unavailable
• Calibrating Noise to Sensitivity in Private Data Analysis→Privacy-preserving data miningLegacy edge — source detail unavailable
• The Algorithmic Foundations of Differential Privacy→Our Data, Ourselves: Privacy Via Distributed Noise GenerationLegacy edge — source detail unavailable
• The Algorithmic Foundations of Differential Privacy→Calibrating Noise to Sensitivity in Private Data AnalysisLegacy edge — source detail unavailable
• Fairness through awareness→Calibrating Noise to Sensitivity in Private Data AnalysisLegacy edge — source detail unavailable
• Differential Privacy: A Survey of Results→Our Data, Ourselves: Privacy Via Distributed Noise GenerationLegacy edge — source detail unavailable
• Differential Privacy: A Survey of Results→Calibrating Noise to Sensitivity in Private Data AnalysisLegacy edge — source detail unavailable
• Differential Privacy: A Survey of Results→Privacy-preserving data miningLegacy edge — source detail unavailable
• (Leveled) fully homomorphic encryption without bootstrapping→Fully homomorphic encryption using ideal latticesLegacy edge — source detail unavailable
• Deep Learning with Differential Privacy→Our Data, Ourselves: Privacy Via Distributed Noise GenerationLegacy edge — source detail unavailable
• Deep Learning with Differential Privacy→Calibrating Noise to Sensitivity in Private Data AnalysisLegacy edge — source detail unavailable
• Deep Learning with Differential Privacy→The Algorithmic Foundations of Differential PrivacyLegacy edge — source detail unavailable
• Deep Learning with Differential Privacy→Model Inversion Attacks that Exploit Confidence Information and Basic CountermeasuresLegacy edge — source detail unavailable
• Deep Learning with Differential Privacy→Privacy-preserving data miningLegacy edge — source detail unavailable
• Deep Learning with Differential Privacy→Adaptive Subgradient Methods for Online Learning and Stochastic OptimizationLegacy edge — source detail unavailable
• Membership Inference Attacks Against Machine Learning Models→Calibrating Noise to Sensitivity in Private Data AnalysisLegacy edge — source detail unavailable
• Membership Inference Attacks Against Machine Learning Models→Model Inversion Attacks that Exploit Confidence Information and Basic CountermeasuresLegacy edge — source detail unavailable
• Membership Inference Attacks Against Machine Learning Models→Deep Learning with Differential PrivacyLegacy edge — source detail unavailable
• Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks→Optimization as a Model for Few-Shot LearningLegacy edge — source detail unavailable
• SecureML: A System for Scalable Privacy-Preserving Machine Learning→Deep Learning with Differential PrivacyLegacy edge — source detail unavailable
• Optimization as a Model for Few-Shot Learning→Adaptive Subgradient Methods for Online Learning and Stochastic OptimizationLegacy edge — source detail unavailable
• Practical Secure Aggregation for Privacy-Preserving Machine Learning→Our Data, Ourselves: Privacy Via Distributed Noise GenerationLegacy edge — source detail unavailable
• Practical Secure Aggregation for Privacy-Preserving Machine Learning→The Algorithmic Foundations of Differential PrivacyLegacy edge — source detail unavailable
• Practical Secure Aggregation for Privacy-Preserving Machine Learning→Model Inversion Attacks that Exploit Confidence Information and Basic CountermeasuresLegacy edge — source detail unavailable
• Practical Secure Aggregation for Privacy-Preserving Machine Learning→Deep Learning with Differential PrivacyLegacy edge — source detail unavailable
• Practical Secure Aggregation for Privacy-Preserving Machine Learning→Membership Inference Attacks Against Machine Learning ModelsLegacy edge — source detail unavailable
• Practical Secure Aggregation for Privacy-Preserving Machine Learning→Communication-Efficient Learning of Deep Networks from Decentralized DataLegacy edge — source detail unavailable
• Federated Machine Learning→Protocols for secure computationsLegacy edge — source detail unavailable
• Federated Machine Learning→Differential Privacy: A Survey of ResultsLegacy edge — source detail unavailable
• Federated Machine Learning→Privacy-preserving data miningLegacy edge — source detail unavailable
• Federated Machine Learning→A Survey on Transfer LearningLegacy edge — source detail unavailable
• Federated Machine Learning→Deep Learning with Differential PrivacyLegacy edge — source detail unavailable
• Federated Machine Learning→SecureML: A System for Scalable Privacy-Preserving Machine LearningLegacy edge — source detail unavailable
• Federated Machine Learning→Practical Secure Aggregation for Privacy-Preserving Machine LearningLegacy edge — source detail unavailable
• Neural Cleanse: Identifying and Mitigating Backdoor Attacks in Neural Networks→Intriguing properties of neural networksLegacy edge — source detail unavailable