id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
fcis-31208	Ye, Minyi; Wu, Lanqing; Zhu, Guanquan; Jiang , Jiaguo	Research on Machine Learning Optimization Algorithm Based on QUBO Model	2025	11	.pdf	application/pdf	5354	231	46	QUBO model can discretize continuous variables (including parameters such as weights and bias) in AR, SVM, CNN and other models in machine learning into binary variables, so as to better deal with nonlinear relationships and reduce the computational complexity in the training process. Flow chart of QUBO model solved by simulated annealing For the parameters in the simulated annealing solver in the Kaiwu SDK, we set them as follows: Select the initial temperature and the end temperature , and select the appropriate cooling coefficient during the annealing process, so that the iterative depth of each temperature in the annealing process does not exceed 100.	cache/fcis-31208.pdf	txt/fcis-31208.txt