Zobrazeno 1 - 10
of 2 512
pro vyhledávání: '"expectile"'
Low-rank matrix factorization is a powerful tool for understanding the structure of 2-way data, and is usually accomplished by minimizing a sum of squares criterion. Expectile analysis generalizes squared-error loss by introducing asymmetry, allowing
Externí odkaz:
http://arxiv.org/abs/2412.04765
Autor:
Almulhim, Fatimah A.1 (AUTHOR) faalmulhim@pnu.edu.sa, Alamari, Mohammed B.2 (AUTHOR) malamari@kku.edu.sa, Rachdi, Mustapha3 (AUTHOR) mustapha.rachdi@univ-grenoble-alpes.fr, Laksaci, Ali2 (AUTHOR) alikfa@kku.edu.sa
Publikováno v:
Mathematics (2227-7390). Dec2024, Vol. 12 Issue 24, p3956. 17p.
Autor:
Bonaccolto-Töpfer, Marina1 (AUTHOR) marina.toepfer@unige.it, Bonaccolto, Giovanni2 (AUTHOR)
Publikováno v:
Journal of Economic Inequality. Sep2023, Vol. 21 Issue 3, p511-535. 25p.
Autor:
Park, Kwanyoung, Lee, Youngwoon
Model-based offline reinforcement learning (RL) is a compelling approach that addresses the challenge of learning from limited, static data by generating imaginary trajectories using learned models. However, these approaches often struggle with inacc
Externí odkaz:
http://arxiv.org/abs/2407.00699
Autor:
Ouhourane, Mohamed1 (AUTHOR) Mohamed.ouhourane@gmail.com, Oualkacha, Karim1 (AUTHOR) oualkacha.karim@uqam.ca, Yang, Archer Yi2 (AUTHOR) archer.yang@mcgill.ca
Publikováno v:
Statistical Methods & Applications. Nov2024, Vol. 33 Issue 5, p1251-1313. 63p.
Autor:
Alamari, Mohammed B.1 (AUTHOR) malamari@kku.edu.sa, Almulhim, Fatimah A.2 (AUTHOR) faalmulhim@pnu.edu.sa, Kaid, Zoulikha1 (AUTHOR) zqayd@kku.edu.sa, Laksaci, Ali1 (AUTHOR) alikfa@kku.edu.sa
Publikováno v:
Axioms (2075-1680). Oct2024, Vol. 13 Issue 10, p678. 22p.
Autor:
Alamari, Mohammed B.1 (AUTHOR) malamari@kku.edu.sa, Almulhim, Fatimah A.2 (AUTHOR) faalmulhim@pnu.edu.sa, Kaid, Zoulikha1 (AUTHOR) zqayd@kku.edu.sa, Laksaci, Ali1 (AUTHOR) alikfa@kku.edu.sa
Publikováno v:
Entropy. Sep2024, Vol. 26 Issue 9, p798. 19p.
Akademický článek
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The systemic risk measure plays a crucial role in analyzing individual losses conditioned on extreme system-wide disasters. In this paper, we provide a unified asymptotic treatment for systemic risk measures. First, we classify them into two families
Externí odkaz:
http://arxiv.org/abs/2404.18029
We present a new approach for Neural Optimal Transport (NOT) training procedure, capable of accurately and efficiently estimating optimal transportation plan via specific regularization on dual Kantorovich potentials. The main bottleneck of existing
Externí odkaz:
http://arxiv.org/abs/2403.03777