Differentially Private Federated Learning: A Client Level Perspective | Paper Citation Record

Observation d15023b4-284e-4d53-8306-774dcdb8afaa · inbound

Federated Learning: Challenges, Methods, and Future Directions cites this paper.

Federated Learning: Challenges, Methods, and Future Directions Differentially Private Federated Learning: A Client Level Perspective

Reference 41

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An End-to-End Encrypted Neural Network for Gradient Updates Transmission in Federated Learning cites this paper.

An End-to-End Encrypted Neural Network for Gradient Updates Transmission in Federated Learning Differentially Private Federated Learning: A Client Level Perspective

Reference 8

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Observation b6b3fd31-630f-4a54-88bf-cf841aba33ca · inbound

Convergent Differential Privacy Analysis for General Federated Learning cites this paper.

Convergent Differential Privacy Analysis for General Federated Learning Differentially Private Federated Learning: A Client Level Perspective

Reference 7

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Act in Collusion: Distributed Multi-Target Backdoor Attacks in Federated Learning cites this paper.

Act in Collusion: Distributed Multi-Target Backdoor Attacks in Federated Learning Differentially Private Federated Learning: A Client Level Perspective

Reference 11

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Observation 70d7e1b6-fca0-4b41-b14b-489b6937193c · inbound

Hidden Data Privacy Breaches in Federated Learning cites this paper.

Hidden Data Privacy Breaches in Federated Learning Differentially Private Federated Learning: A Client Level Perspective

Reference 19

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Observation 3feea60a-bd28-41f8-aa06-959f9a8d91ea · inbound

Upcycling Noise for Federated Unlearning cites this paper.

Upcycling Noise for Federated Unlearning Differentially Private Federated Learning: A Client Level Perspective

Reference 5

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Observation 73960480-86fb-4036-bd37-2915c249df7d · inbound

Membership Inference Attacks and Defenses in Federated Learning: A Survey cites this paper.

Membership Inference Attacks and Defenses in Federated Learning: A Survey Differentially Private Federated Learning: A Client Level Perspective

Reference 42

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Observation f651cf50-90db-48d5-ac77-d7d48191282e · inbound

A New Federated Learning Framework Against Gradient Inversion Attacks cites this paper.

A New Federated Learning Framework Against Gradient Inversion Attacks Differentially Private Federated Learning: A Client Level Perspective

Reference 2020

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Observation 668c13aa-ed2d-47bd-a88e-ea62df4996f1 · inbound

Generalising Battery Control in Net-Zero Buildings via Personalised Federated RL cites this paper.

Generalising Battery Control in Net-Zero Buildings via Personalised Federated RL Differentially Private Federated Learning: A Client Level Perspective

Reference 12

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Observation 64fbe8ac-3a15-4747-9595-aa7029fedc8b · inbound

Multi-Modal One-Shot Federated Ensemble Learning for Medical Data with Vision Large Language Model cites this paper.

Multi-Modal One-Shot Federated Ensemble Learning for Medical Data with Vision Large Language Model Differentially Private Federated Learning: A Client Level Perspective

Reference 7

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Observation ad8f12db-d41e-492a-870e-8774a710c129 · inbound

TAPFed: Threshold Secure Aggregation for Privacy-Preserving Federated Learning cites this paper.

TAPFed: Threshold Secure Aggregation for Privacy-Preserving Federated Learning Differentially Private Federated Learning: A Client Level Perspective

Reference 20

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Observation 5d752747-59ea-45a4-9508-0e87b25f472e · inbound

CENSOR: Defense Against Gradient Inversion via Orthogonal Subspace Bayesian Sampling cites this paper.

CENSOR: Defense Against Gradient Inversion via Orthogonal Subspace Bayesian Sampling Differentially Private Federated Learning: A Client Level Perspective

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-10T14:05:45.474399Z

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Observation edd96140-6f9e-433e-923d-277c7fc9ce31 · inbound

Metric Privacy in Federated Learning for Medical Imaging: Improving Convergence and Preventing Client Inference Attacks cites this paper.

Metric Privacy in Federated Learning for Medical Imaging: Improving Convergence and Preventing Client Inference Attacks Differentially Private Federated Learning: A Client Level Perspective

Reference 32

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Observation cdd581d1-f8c7-4b8f-907b-d76eee1218a7 · inbound

Private Federated Learning In Real World Application -- A Case Study cites this paper.

Private Federated Learning In Real World Application -- A Case Study Differentially Private Federated Learning: A Client Level Perspective

Reference 6

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Observation e092bdc1-eba7-46b0-ae80-4acd1d2ecd7b · inbound

Towards One-shot Federated Learning: Advances, Challenges, and Future Directions cites this paper.

Towards One-shot Federated Learning: Advances, Challenges, and Future Directions Differentially Private Federated Learning: A Client Level Perspective

Reference 30

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Observation b1ed5a4f-61cf-4965-8168-140dd30e5d5a · inbound

Efficient Full-Stack Private Federated Deep Learning with Post-Quantum Security cites this paper.

Efficient Full-Stack Private Federated Deep Learning with Post-Quantum Security Differentially Private Federated Learning: A Client Level Perspective

Reference 34

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Observation 8ce63254-b83b-431d-81f0-14fdcf947336 · inbound

RiM: Record, Improve and Maintain Physical Well-being using Federated Learning cites this paper.

RiM: Record, Improve and Maintain Physical Well-being using Federated Learning Differentially Private Federated Learning: A Client Level Perspective

Reference 10

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Observation 8dd7e283-a87c-4e6b-abb7-3e75c8e75c55 · inbound

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning cites this paper.

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning Differentially Private Federated Learning: A Client Level Perspective

Reference 2011

Resolution: unresolved; no resolver link, observed 2026-08-15T21:24:27.418740Z

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Observation 72cf0221-0c1b-4698-a72a-e62cb78de670 · inbound

Enhancing Federated Survival Analysis through Peer-Driven Client Reputation in Healthcare cites this paper.

Enhancing Federated Survival Analysis through Peer-Driven Client Reputation in Healthcare Differentially Private Federated Learning: A Client Level Perspective

Reference 24

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Observation aef27a2f-9170-4322-956a-92afbe77c20d · inbound

LAPA-based Dynamic Privacy Optimization for Wireless Federated Learning in Heterogeneous Environments cites this paper.

LAPA-based Dynamic Privacy Optimization for Wireless Federated Learning in Heterogeneous Environments Differentially Private Federated Learning: A Client Level Perspective

Reference 22

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Observation d4f64195-8ae1-497a-89bc-b63526b4e08f · inbound

Boosting Gradient Leakage Attacks: Data Reconstruction in Realistic FL Settings cites this paper.

Boosting Gradient Leakage Attacks: Data Reconstruction in Realistic FL Settings Differentially Private Federated Learning: A Client Level Perspective

Reference 23

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Observation 5ffbe337-42b4-4891-82f6-e8ae37b76b2d · inbound

Shadow defense against gradient inversion attack in federated learning cites this paper.

Shadow defense against gradient inversion attack in federated learning Differentially Private Federated Learning: A Client Level Perspective

Reference 13

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Observation cc1e4288-0969-471a-a861-7ffc14400d8f · inbound

Decoding Federated Learning: The FedNAM+ Conformal Revolution cites this paper.

Decoding Federated Learning: The FedNAM+ Conformal Revolution Differentially Private Federated Learning: A Client Level Perspective

Reference 7

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Observation 8dda28a6-d7a4-4ee8-a5b1-0afb74a2d6e0 · inbound

Asymptotically Optimal Secure Aggregation for Wireless Federated Learning with Multiple Servers cites this paper.

Asymptotically Optimal Secure Aggregation for Wireless Federated Learning with Multiple Servers Differentially Private Federated Learning: A Client Level Perspective

Reference 13

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Observation 7d0775e9-3344-4ff9-908a-bf159ae6e391 · inbound

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning cites this paper.

One-Bit Model Aggregation for Differentially Private and Byzantine-Robust Personalized Federated Learning Differentially Private Federated Learning: A Client Level Perspective

Reference 33

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Observation 32512c88-49ef-4f07-9ca8-662973f22cc0 · inbound

DRAGD: A Federated Unlearning Data Reconstruction Attack Based on Gradient Differences cites this paper.

DRAGD: A Federated Unlearning Data Reconstruction Attack Based on Gradient Differences Differentially Private Federated Learning: A Client Level Perspective

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-06T17:56:02.209538Z

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Observation ee14e768-f366-417b-9fde-256510f1806a · inbound

Learning Private Representations through Entropy-based Adversarial Training cites this paper.

Learning Private Representations through Entropy-based Adversarial Training Differentially Private Federated Learning: A Client Level Perspective

Reference 18

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Observation a4d66d83-0877-41ef-b4a9-2bba0545bab6 · inbound

Convergence of Agnostic Federated Averaging cites this paper.

Convergence of Agnostic Federated Averaging Differentially Private Federated Learning: A Client Level Perspective

Reference 12

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Observation 4ff63e87-c214-4528-9dca-e65f26c03c34 · inbound

FLsim: A Modular and Library-Agnostic Simulation Framework for Federated Learning cites this paper.

FLsim: A Modular and Library-Agnostic Simulation Framework for Federated Learning Differentially Private Federated Learning: A Client Level Perspective

Reference 7

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Observation 918812a0-c553-4d5a-9687-d2e3cb604bae · inbound

FedGA: A Fair Federated Learning Framework Based on the Gini Coefficient cites this paper.

FedGA: A Fair Federated Learning Framework Based on the Gini Coefficient Differentially Private Federated Learning: A Client Level Perspective

Reference 6

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Observation 81830f7c-080c-4423-ad09-aa23a3b8270d · inbound

Cyst-X: A Multi-Center MRI Benchmark and Federated Learning Framework for Malignancy-Risk Stratification of Pancreatic Cystic Neoplasm cites this paper.

Cyst-X: A Multi-Center MRI Benchmark and Federated Learning Framework for Malignancy-Risk Stratification of Pancreatic Cystic Neoplasm Differentially Private Federated Learning: A Client Level Perspective

Reference 46

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Observation 07fe34b7-7032-4c4c-97a5-b938e81857e1 · inbound

A Systematic Survey of Model Extraction Attacks and Defenses: State-of-the-Art and Perspectives cites this paper.

A Systematic Survey of Model Extraction Attacks and Defenses: State-of-the-Art and Perspectives Differentially Private Federated Learning: A Client Level Perspective

Reference 63

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Observation 35b3afdb-7129-40c2-8293-8bac4cdc2d45 · inbound

Enhancing Model Privacy in Federated Learning with Random Masking and Quantization cites this paper.

Enhancing Model Privacy in Federated Learning with Random Masking and Quantization Differentially Private Federated Learning: A Client Level Perspective

Reference 14

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Observation f19e4b4a-e1d5-4eb8-831b-99b00cd7a8b7 · inbound

Sketched Gaussian Mechanism for Private Federated Learning cites this paper.

Sketched Gaussian Mechanism for Private Federated Learning Differentially Private Federated Learning: A Client Level Perspective

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-04T21:12:50.309059Z

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Observation 6fa13caa-f8d8-415e-85bd-f645f35aaab7 · inbound

FedRP: A Communication-Efficient Approach for Differentially Private Federated Learning Using Random Projection cites this paper.

FedRP: A Communication-Efficient Approach for Differentially Private Federated Learning Using Random Projection Differentially Private Federated Learning: A Client Level Perspective

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-04T18:23:48.601284Z

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Observation f9ce7cee-ec46-4ef4-9be3-ed9f1fd36de9 · inbound

Differentially Private Decentralized Dataset Synthesis Through Randomized Mixing with Correlated Noise cites this paper.

Differentially Private Decentralized Dataset Synthesis Through Randomized Mixing with Correlated Noise Differentially Private Federated Learning: A Client Level Perspective

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-04T18:03:12.740476Z

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Observation 6f2c8bbb-f734-4b67-8a68-046e895fbfc5 · inbound

PrivacyBench: Privacy Isn't Free in Hybrid Privacy-Preserving Vision Systems cites this paper.

PrivacyBench: Privacy Isn't Free in Hybrid Privacy-Preserving Vision Systems Differentially Private Federated Learning: A Client Level Perspective

Reference 23

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Observation f5fec328-8636-4e7c-8e32-6346a3c2a0be · inbound

Compliance Management for Federated Data Processing cites this paper.

Compliance Management for Federated Data Processing Differentially Private Federated Learning: A Client Level Perspective

Reference 21

Resolution: metadata mismatch; local_arxiv, observed 2026-05-15T20:06:33.914897Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ffdc6a11-e051-4e44-addd-365c29ac8b77 · inbound

DP-FedAdamW: An Efficient Optimizer for Differentially Private Federated Large Models cites this paper.

DP-FedAdamW: An Efficient Optimizer for Differentially Private Federated Large Models Differentially Private Federated Learning: A Client Level Perspective

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-05-15T20:06:34.004610Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 94a1e4cf-98e6-4ad9-b87c-71193b128b1f · inbound

Practical Quantum Federated Learning for Privacy-Sensitive Healthcare: Communication Efficiency and Noise Resilience cites this paper.

Practical Quantum Federated Learning for Privacy-Sensitive Healthcare: Communication Efficiency and Noise Resilience Differentially Private Federated Learning: A Client Level Perspective

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-05-15T17:30:11.008881Z

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Observation a6951837-d5a5-4430-8758-092a27936ce7 · inbound

FedSpy-LLM: Towards Scalable and Generalizable Data Reconstruction Attacks from Gradients on LLMs cites this paper.

FedSpy-LLM: Towards Scalable and Generalizable Data Reconstruction Attacks from Gradients on LLMs Differentially Private Federated Learning: A Client Level Perspective

Reference 43

Resolution: verified exact; arxiv_id, observed 2026-05-10T23:30:51.316758Z

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Observation 75eac8f4-b077-4216-88b3-688de3b2616b · inbound

Scalable and Private Federated Learning Using Distributed Differential Privacy and Secure Aggregation cites this paper.

Scalable and Private Federated Learning Using Distributed Differential Privacy and Secure Aggregation Differentially Private Federated Learning: A Client Level Perspective

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:51:11.033603Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6b4e7540-61c8-4454-96c4-b11e86745406 · inbound

Federated Cross-Modal Retrieval with Missing Modalities via Semantic Routing and Adapter Personalization cites this paper.

Federated Cross-Modal Retrieval with Missing Modalities via Semantic Routing and Adapter Personalization Differentially Private Federated Learning: A Client Level Perspective

Reference 10

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T19:06:09.327341Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0c4803e3-60ea-4bd8-9ea8-94d7e400f4ee · inbound

Enhanced Privacy and Communication Efficiency in Non-IID Federated Learning with Adaptive Quantization and Differential Privacy cites this paper.

Enhanced Privacy and Communication Efficiency in Non-IID Federated Learning with Adaptive Quantization and Differential Privacy Differentially Private Federated Learning: A Client Level Perspective

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:41:09.490081Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation df0f0c8d-e59c-4e5e-bf90-be4167df13fc · inbound

Taming Noise-Induced Prototype Degradation for Privacy-Preserving Personalized Federated Fine-Tuning cites this paper.

Taming Noise-Induced Prototype Degradation for Privacy-Preserving Personalized Federated Fine-Tuning Differentially Private Federated Learning: A Client Level Perspective

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-12T10:16:28.609225Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 94401695-3ea0-4c8a-8abd-745ec0fa65e9 · inbound

DP-LAC: Lightweight Adaptive Clipping for Differentially Private Federated Fine-tuning of Language Models cites this paper.

DP-LAC: Lightweight Adaptive Clipping for Differentially Private Federated Fine-tuning of Language Models Differentially Private Federated Learning: A Client Level Perspective

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-12T05:31:25.490303Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e1f8f3a1-3f54-4d4a-91da-afc95a55f408 · inbound

Statistical Limits and Efficient Algorithms for Differentially Private Federated Learning cites this paper.

Statistical Limits and Efficient Algorithms for Differentially Private Federated Learning Differentially Private Federated Learning: A Client Level Perspective

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-05-20T08:03:08.749301Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d20eec1a-d444-40c7-a0b1-13f8c3b1b0f5 · inbound

DIST-FL: Enhancing Security for TEE-based Aggregation in Federated Learning cites this paper.

DIST-FL: Enhancing Security for TEE-based Aggregation in Federated Learning Differentially Private Federated Learning: A Client Level Perspective

Reference 71

Resolution: verified exact; local_arxiv, observed 2026-07-02T08:46:49.029587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 41accbff-43f0-4cc9-85ba-34db9b9f500c · inbound

CausShield: Sample Reconstruction-Resilient Vertical FL via Causal Representation Learning cites this paper.

CausShield: Sample Reconstruction-Resilient Vertical FL via Causal Representation Learning Differentially Private Federated Learning: A Client Level Perspective

Reference 35

Resolution: verified exact; local_arxiv, observed 2026-07-02T20:47:22.692588Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 22c05d23-d194-4828-a1f7-3cbfec895d56 · inbound

TIGER: Inverting Transformer Gradients via Embedding-Subspace Distance Optimization cites this paper.

TIGER: Inverting Transformer Gradients via Embedding-Subspace Distance Optimization Differentially Private Federated Learning: A Client Level Perspective

Reference 52

Resolution: metadata mismatch; local_arxiv, observed 2026-07-03T21:28:59.414787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8df638de-3020-45c0-881f-ffe099c62c51 · inbound

Robust Federated Learning Under Real-World Client Churn cites this paper.

Robust Federated Learning Under Real-World Client Churn Differentially Private Federated Learning: A Client Level Perspective

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-07-09T22:36:36.205489Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b46d0228-51a2-426d-916f-61354efd2f5b · inbound

Collaborative Synthetic Data Generation for Knowledge Transfer in Federated Learning cites this paper.

Collaborative Synthetic Data Generation for Knowledge Transfer in Federated Learning Differentially Private Federated Learning: A Client Level Perspective

Reference 17

Resolution: metadata mismatch; local_arxiv, observed 2026-07-09T07:06:02.905449Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6562af71-9cb0-429d-b290-dbe3be7fa474 · inbound

Threat Vectors and the State of the Art in Defense Methods for Security in Neurotechnology cites this paper.

Threat Vectors and the State of the Art in Defense Methods for Security in Neurotechnology Differentially Private Federated Learning: A Client Level Perspective

Reference 149

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Observation 0f610441-7606-4136-b89d-04ef367625f2 · inbound

Fairis: Fairness-Aware Aggregation with Provable Influence Containment against Fairness Poisoning Attacks in Collaborative Machine Learning cites this paper.

Fairis: Fairness-Aware Aggregation with Provable Influence Containment against Fairness Poisoning Attacks in Collaborative Machine Learning Differentially Private Federated Learning: A Client Level Perspective

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-15T14:37:19.006120Z

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Observation caa398ed-63f2-4614-990f-878232954760 · inbound

Personalized Federated Learning via Variance-Aware Nonparametric Empirical Bayes cites this paper.

Personalized Federated Learning via Variance-Aware Nonparametric Empirical Bayes Differentially Private Federated Learning: A Client Level Perspective

Reference 135

Resolution: unresolved; no resolver link, observed 2026-08-12T00:13:13.928867Z

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