Right to be Forgotten - Edgentiq

Ensuring Data Privacy: A Framework for Verifiable Federated Unlearning

Verifying Data Removal in AI Models with Self-supervised Seeding

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New Algorithm Enables Flexible Data Removal in Tree Ensemble Models

Efficient Data Erasure: Machine Unlearning’s Role in Medical AI Privacy

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New Framework Addresses Data Forgetting in Federated Learning with Information Theory

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Un-pruning: Enabling Data Forgetting in the Structure of Sparse AI Models

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Ensuring Data Privacy: A Framework for Verifiable Federated Unlearning

October 2, 2025

Verifying Data Removal in AI Models with Self-supervised Seeding

October 1, 2025

Protecting Code Language Models from Sensitive Data Leaks with Targeted Unlearning

September 18, 2025