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Jiaxin Deng

2 papers indexed

arxivcs.LGcs.AI2026-07-24

From Perturbation Correction to Geometry-Aware Sampling: Sharpness-Guided Equilibrium Sampling for Balanced Flat Minima in Long-Tailed Learning

Jiaxin Deng, Junbiao Pang

Long-tailed learning couples two sources of poor generalization: head classes dominate training exposure, while under-represented classes often converge to sharper regions of the loss landscape. Conventional re-sampling addresses the former without considering geometry, whereas e…

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arxivcs.LGcs.AI2026-07-17

Gradient-Energy Guided Block-Wise Perturbations for Sharpness-Aware Minimization

Zhen Huang, Jiaxin Deng, Junbiao Pang

Sharpness-Aware Minimization (SAM) improves generalization by minimizing the worst-case loss in a local parameter neighborhood. Standard SAM implicitly allocates its global perturbation budget across parameter blocks according to instantaneous minibatch gradient norms. Such an al…

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