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cs.LG2024
How Transformers Get Rich: Approximation and Dynamics Analysis
Mingze Wang, Ruoxi Yu, Weinan E +1
Transformers have demonstrated exceptional in-context learning capabilities, yet the theoretical understanding of the underlying mechanisms remains limited. A recent work (Elhage e…
cs.LG2024
Improving Generalization and Convergence by Enhancing Implicit Regularization
Mingze Wang, Jinbo Wang, Haotian He +6
In this work, we propose an Implicit Regularization Enhancement (IRE) framework to accelerate the discovery of flat solutions in deep learning, thereby improving generalization and…
cs.LG2024
Parameter Symmetry and Noise Equilibrium of Stochastic Gradient Descent
Liu Ziyin, Mingze Wang, Hongchao Li +1
Symmetries are prevalent in deep learning and can significantly influence the learning dynamics of neural networks. In this paper, we examine how exponential symmetries -- a broad…