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cs.LG2026
Forgetting Similar Samples: Can Machine Unlearning Do it Better?
Heng Xu, Tianqing Zhu, Dayong Ye +3
Machine unlearning, a process enabling pre-trained models to remove the influence of specific training samples, has attracted significant attention in recent years. Although extens…
cs.LG2021★ 1 cited
Unified Regularity Measures for Sample-wise Learning and Generalization
Chi Zhang, Xiaoning Ma, Yu Liu +3
Fundamental machine learning theory shows that different samples contribute unequally both in learning and testing processes. Contemporary studies on DNN imply that such sample dif…
cs.LG2021
Practical Relative Order Attack in Deep Ranking
Mo Zhou, Le Wang, Zhenxing Niu +4
Recent studies unveil the vulnerabilities of deep ranking models, where an imperceptible perturbation can trigger dramatic changes in the ranking result. While previous attempts fo…