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Junyu Zhou

2 accepted papers

2026

Optimization, Generalization and Differential Privacy Bounds for Gradient Descent on Kolmogorov–Arnold Networks

ICML 2026poster

Kolmogorov--Arnold Networks (KANs) have recently emerged as a structured alternative to standard MLPs, yet a principled theory for their training dynamics, generalization, and privacy properties remains limited. In this paper, we analyze gradient descent (GD) for training two-layer KANs and derive g…

Cited by 0SourceScholar
2025

Diffusion-Driven Progressive Target Manipulation for Source-Free Domain Adaptation

NeurIPS 2025poster

Source-free domain adaptation (SFDA) is a challenging task that tackles domain shifts using only a pre-trained source model and unlabeled target data. Existing SFDA methods are restricted by the fundamental limitation of source-target domain discrepancy. Non-generation SFDA methods suffer from unrel…

Cited by 0SourceScholar