9 citations · 14 across the 16 of their papers we have counts for
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cs.LG2025
AlignFlow: Improving Flow-based Generative Models with Semi-Discrete Optimal Transport
Lingkai Kong, Molei Tao, Yang Liu +4
Flow-based Generative Models (FGMs) effectively transform noise into complex data distributions. Incorporating Optimal Transport (OT) to couple noise and data during FGM training h…
cs.LG2023
KD-FixMatch: Knowledge Distillation Siamese Neural Networks
Chien-Chih Wang, Shaoyuan Xu, Jinmiao Fu +2
Semi-supervised learning (SSL) has become a crucial approach in deep learning as a way to address the challenge of limited labeled data. The success of deep neural networks heavily…
cs.LG2023★ 1 cited
AdaSelection: Accelerating Deep Learning Training through Data Subsampling
Minghe Zhang, Chaosheng Dong, Jinmiao Fu +8
In this paper, we introduce AdaSelection, an adaptive sub-sampling method to identify the most informative sub-samples within each minibatch to speed up the training of large-scale…