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cs.LG2026
Perturbation-Induced Linearization: Constructing Unlearnable Data with Solely Linear Classifiers
Jinlin Liu, Wei Chen, Xiaojin Zhang
Collecting web data to train deep models has become increasingly common, raising concerns about unauthorized data usage. To mitigate this issue, unlearnable examples introduce impe…
cs.LG2025
FedEM: A Privacy-Preserving Framework for Concurrent Utility Preservation in Federated Learning
Mingcong Xu, Xiaojin Zhang, Wei Chen +1
Federated Learning (FL) enables collaborative training of models across distributed clients without sharing local data, addressing privacy concerns in decentralized systems. Howeve…
cs.LG2025
FedEAT: A Robustness Optimization Framework for Federated LLMs
Yahao Pang, Xingyuan Wu, Xiaojin Zhang +2
Significant advancements have been made by Large Language Models (LLMs) in the domains of natural language understanding and automated content creation. However, they still face pe…