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pro vyhledávání: '"Karimi, Sahar"'
Bayesian Neural Networks (BNN) have emerged as a crucial approach for interpreting ML predictions. By sampling from the posterior distribution, data scientists may estimate the uncertainty of an inference. Unfortunately many inference samples are oft
Externí odkaz:
http://arxiv.org/abs/2311.13036
Publikováno v:
In International Journal of Production Economics August 2024 274
Autor:
Karimi, Sahar, Vavasis, Stephen
The method of nonlinear conjugate gradients (NCG) is widely used in practice for unconstrained optimization, but it satisfies weak complexity bounds at best when applied to smooth convex functions. In contrast, Nesterov's accelerated gradient (AG) me
Externí odkaz:
http://arxiv.org/abs/2111.11613
Autor:
Mrad, Mona1 (AUTHOR) mmrad@aus.edu, Karimi, Sahar2 (AUTHOR), Tóth, Zsófia3 (AUTHOR), Christodoulides, George1 (AUTHOR)
Publikováno v:
Journal of Marketing Management. Oct2022, Vol. 38 Issue 13/14, p1339-1368. 30p. 1 Diagram, 2 Charts.
Publikováno v:
In Journal of Business Research February 2023 156
Akademický článek
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Autor:
Karimi, Sahar, Vavasis, Stephen
Nesterov's accelerated gradient (AG) method for minimizing a smooth strongly convex function $f$ is known to reduce $f({\bf x}_k)-f({\bf x}^*)$ by a factor of $\epsilon\in(0,1)$ after $k=O(\sqrt{L/\ell}\log(1/\epsilon))$ iterations, where $\ell,L$ ar
Externí odkaz:
http://arxiv.org/abs/1712.09498
Autor:
Karimi, Sahar, Ronagh, Pooya
Publikováno v:
Quantum Information Processing, Vol. 18, No. 4, 94 (2019)
Recent advancements in quantum annealing hardware and numerous studies in this area suggests that quantum annealers have the potential to be effective in solving unconstrained binary quadratic programming problems. Naturally, one may desire to expand
Externí odkaz:
http://arxiv.org/abs/1706.01945
Publikováno v:
Psychology & Marketing; Jul2024, Vol. 41 Issue 7, p1549-1561, 13p
Autor:
Karimi, Sahar
In a series of work initiated by Nemirovsky and Yudin, and later extended by Nesterov, first-order algorithms for unconstrained minimization with optimal theoretical complexity bound have been proposed. On the other hand, conjugate gradient algorithm
Externí odkaz:
http://hdl.handle.net/10012/8189