From Optimization to Sampling Through Gradient Flows
From Optimization to Sampling Through Gradient Flows
复制标题
从优化到梯度流采样
DOI:
10.1090/noti2717
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发表时间:
2023
影响因子:
--
通讯作者:
Sanz-Alonso, D
中科院分区:
文献类型:
--
作者:
García Trillos, N;Hosseini, B;Sanz-Alonso, D
Optimization and sampling algorithms play a central role in science and engineering as they enable finding optimal predictions, policies, and recommendations, as well as expected and equilibrium states of complex systems. The notion of “optimality” is formalized by the choice of an objective function, while the notion of an “expected” state is specified by a probabilistic model for the distribution of states. Optimizing rugged objective functions and sampling multimodal distributions is computationally challenging, especially in high-dimensional problems. For this reason, many optimization and sampling methods have
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DOI:
10.1002/9780470549124.ch1
发表时间:
2019-10
期刊:
Optimization for Chemical and Biochemical Engineering
影响因子:
--
作者:
Xin-She Yang;Xingshi He
通讯作者:
Xin-She Yang;Xingshi He
DOI:
--
发表时间:
2020-05
期刊:
ArXiv
影响因子:
--
作者:
Sinho Chewi;Thibaut Le Gouic;Chen Lu;Tyler Maunu;P. Rigollet;Austin J. Stromme
通讯作者:
Sinho Chewi;Thibaut Le Gouic;Chen Lu;Tyler Maunu;P. Rigollet;Austin J. Stromme
DOI:
10.1137/19m1251655
发表时间:
2019-03
期刊:
SIAM J. Appl. Dyn. Syst.
影响因子:
--
作者:
A. Garbuno-Iñigo;F. Hoffmann;Wuchen Li;A. Stuart
通讯作者:
A. Garbuno-Iñigo;F. Hoffmann;Wuchen Li;A. Stuart
影响因子:
6
作者:
Kovachki, Nikola;Stuart, Andrew M.
通讯作者:
Stuart, Andrew M.