AI RESEARCH
Evolution of Optimization Methods: Algorithms, Scenarios, and Evaluations
arXiv CS.LG
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ArXi:2604.12968v1 Announce Type: new Balancing convergence speed, generalization capability, and computational efficiency remains a core challenge in deep learning optimization. First-order gradient descent methods, epitomized by stochastic gradient descent (SGD) and Adam, serve as the cornerstone of modern