3 accepted papers
Momentum-based optimizers are widely adopted for training neural networks. However, the optimal selection of momentum coefficients remains elusive. This uncertainty impedes a clear understanding of the role of momentum in stochastic gradient methods. In this paper, we present a frequency domain anal…
Simulation of high-order nonlinear system requires extensive computational resources, especially in modern VLSI backend design where bifurcation-induced instability and chaos-like transient behaviors pose challenges. We present S-Crescendo - a nested transformer weaving framework that synergizes S-d…
Hospitals worldwide share common challenges in finding the optimal number of patient beds in advance, which is referred to as the bed capacity management problem. Effective management cannot be achieved without an appropriate understanding of the stochastic nature of patient demands. In light of the