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cs.LG2025
Pushing the Limits of Low-Bit Optimizers: A Focus on EMA Dynamics
Cong Xu, Wenbin Liang, Mo Yu +7
The rapid scaling of models has led to prohibitively high training and fine-tuning costs. A major factor accounting for memory consumption is the widespread use of stateful optimiz…
cs.LG2023★ 22 cited
Learning Interpretable Rules for Scalable Data Representation and Classification
Zhuo Wang, Wei Zhang, Ning Liu +1
Rule-based models, e.g., decision trees, are widely used in scenarios demanding high model interpretability for their transparent inner structures and good model expressivity. Howe…