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cs.LG2026
Pairing Regularization for Mitigating Many-to-One Collapse in GANs
Kuan-Yu Lin, Yu-Chih Huang, Tie Liu
Mode collapse remains a fundamental challenge in training generative adversarial networks (GANs). While existing works have primarily focused on inter-mode collapse, such as mode d…
cs.LG2024
Age Aware Scheduling for Differentially-Private Federated Learning
Kuan-Yu Lin, Hsuan-Yin Lin, Yu-Pin Hsu +1
This paper explores differentially-private federated learning (FL) across time-varying databases, delving into a nuanced three-way tradeoff involving age, accuracy, and differentia…