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cs.LG2023
Model Provenance via Model DNA
Xin Mu, Yu Wang, Yehong Zhang +4
Understanding the life cycle of the machine learning (ML) model is an intriguing area of research (e.g., understanding where the model comes from, how it is trained, and how it is…
cs.LG2022★ 2 cited
Nebula-I: A General Framework for Collaboratively Training Deep Learning Models on Low-Bandwidth Cloud Clusters
Yang Xiang, Zhihua Wu, Weibao Gong +15
The ever-growing model size and scale of compute have attracted increasing interests in training deep learning models over multiple nodes. However, when it comes to training on clo…