Zobrazeno 1 - 10
of 227
pro vyhledávání: '"Wotao Yin"'
Publikováno v:
Fixed Point Theory and Algorithms for Sciences and Engineering, Vol 2021, Iss 1, Pp 1-19 (2021)
Abstract Inverse problems consist of recovering a signal from a collection of noisy measurements. These problems can often be cast as feasibility problems; however, additional regularization is typically necessary to ensure accurate and stable recove
Externí odkaz:
https://doaj.org/article/44f7425af370421a908ad4da0f3a81fc
Publikováno v:
SIAM Journal on Optimization; 2024, Vol. 34 Issue 2, p1206-1235, 30p
Publikováno v:
SIAM Journal on Mathematics of Data Science. 4:581-603
Inverse problems consist of recovering a signal from a collection of noisy measurements. These are typically cast as optimization problems, with classic approaches using a data fidelity term and an analytic regularizer that stabilizes recovery. Recen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d9d2362ad9c511dfe1b32f690e53fee3
https://doi.org/10.1137/20m1376790
https://doi.org/10.1137/20m1376790
Publikováno v:
IEEE Transactions on Power Systems. 37:2455-2458
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::580e91ecdc71d2caa852cb638443d7be
https://doi.org/10.1109/tpwrs.2022.3146772
https://doi.org/10.1109/tpwrs.2022.3146772
Publikováno v:
SIAM Journal on Optimization. 32:687-714
We consider the problem of minimizing a high-dimensional objective function, which may include a regularization term, using (possibly noisy) evaluations of the function. Such optimization is also called derivative-free, zeroth-order, or black-box opt
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::aacd299fc40effb81718db16b4e58e83
https://doi.org/10.1137/21m1392966
https://doi.org/10.1137/21m1392966
Autor:
Ernest K. Ryu, Wotao Yin
Starting from where a first course in convex optimization leaves off, this text presents a unified analysis of first-order optimization methods – including parallel-distributed algorithms – through the abstraction of monotone operators. With the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3ca876efab8bb58dcdbf136c39a071b8
https://doi.org/10.1017/9781009160865
https://doi.org/10.1017/9781009160865
Autor:
Ryu, Ernest K.1 eryu@math.ucla.edu, Wotao Yin1 wotaoyin@math.ucla.edu
Publikováno v:
Journal of Computational Mathematics. 2019, Vol. 37 Issue 6, p778-812. 35p.
Publikováno v:
Mathematical Programming. 195:421-473
This paper considers the problem of solving a special quartic–quadratic optimization problem with a single sphere constraint, namely, finding a global and local minimizer of $$\frac{1}{2}\mathbf {z}^{*}A\mathbf {z}+\frac{\beta }{2}\sum _{k=1}^{n}|z
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6d94bd9ef9679935b2c62809ad60fb81
https://doi.org/10.1007/s10107-021-01702-6
https://doi.org/10.1007/s10107-021-01702-6
Publikováno v:
Mathematical Programming. 194:569-619
Many iterative methods in applied mathematics can be thought of as fixed-point iterations, and such algorithms are usually analyzed analytically, with inequalities. In this paper, we present a geometric approach to analyzing contractive and nonexpans
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2e57a200a5182b53bcdc5c1fd905e7ca
https://doi.org/10.1007/s10107-021-01639-w
https://doi.org/10.1007/s10107-021-01639-w
Publikováno v:
IEEE Transactions on Signal Processing. 69:6055-6070
Federated Learning (FL) is popular for communication-efficient learning from distributed data. To utilize data at different clients without moving them to the cloud, algorithms such as the Federated Averaging (FedAvg) have adopted a computation then
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::406fd31008e1b15f4b683cf0d351153a
https://doi.org/10.1109/tsp.2021.3115952
https://doi.org/10.1109/tsp.2021.3115952