scholarly journals Design of First-Order Optimization Algorithms via Sum-of-Squares Programming

Author(s):  
Mahyar Fazlyab ◽  
Manfred Morari ◽  
Victor M. Preciado
2020 ◽  
Vol 34 (10) ◽  
pp. 13935-13936
Author(s):  
Tato Ange ◽  
Nkambou Roger

This paper presents a simple and intuitive technique to accelerate the convergence of first-order optimization algorithms. The proposed solution modifies the update rule, based on the variation of the direction of the gradient and the previous step taken during training. Results after tests show that the technique has the potential to significantly improve the performance of existing first-order optimization algorithms.


2020 ◽  
Vol 108 (11) ◽  
pp. 2067-2082
Author(s):  
Huan Li ◽  
Cong Fang ◽  
Zhouchen Lin

2021 ◽  
pp. 1-10
Author(s):  
Jing Zhang ◽  
Yuhong Sheng ◽  
Xiaoli Wang

Parameter estimation of high-order uncertain differential equations is an inevitable problem in practice. In this paper, the equivalent equations of high-order uncertain differential equations are obtained by transformation, and the parameters of the first-order uncertain differential equation including Liu process are estimated. Based on the least squares estimation method, this paper proposes a means to minimize the residual sum of squares to obtain an estimate of the parameters in the drift term, and make the noise sum of squares equal to the residual sum of squares to obtain an estimate of the parameters in the diffusion term. In addition, some numerical examples are given to illustrate the proposed method. Finally, applications of the high-order uncertain spring vibration equations verify the viability of our method.


Optimization ◽  
2021 ◽  
pp. 1-40
Author(s):  
Hedy Attouch ◽  
Zaki Chbani ◽  
Jalal Fadili ◽  
Hassan Riahi

Author(s):  
Sandra S. Y. Tan ◽  
Antonios Varvitsiotis ◽  
Vincent Y. F. Tan

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