Zobrazeno 1 - 10
of 532
pro vyhledávání: '"Rhee, Chang"'
Autor:
Su, Zhe, Rhee, Chang-Han
The large deviations theory for heavy-tailed processes has seen significant advances in the recent past. In particular, Rhee et al. (2019) and Bazhba et al. (2020) established large deviation asymptotics at the sample-path level for L\'evy processes
Externí odkaz:
http://arxiv.org/abs/2410.20799
Autor:
Wang, Xingyu, Rhee, Chang-Han
In this paper, we address rare-event simulation for heavy-tailed L\'evy processes with infinite activities. The presence of infinite activities poses a critical challenge, making it impractical to simulate or store the precise sample path of the L\'e
Externí odkaz:
http://arxiv.org/abs/2309.13820
Autor:
Wang, Xingyu, Rhee, Chang-Han
This paper introduces novel frameworks for large deviations and metastability analysis in heavy-tailed stochastic dynamical systems. We develop and apply these frameworks within the context of stochastic difference equation $X^\eta_{j+1}(x) = X^\eta_
Externí odkaz:
http://arxiv.org/abs/2307.03479
Autor:
Jeong, Wonjong, Chun, Young-Bum, Kang, Suk Hoon, Rhee, Chang Kyu, Yoo, Chang Hyoung, Yoo, Seongjin, Kim, Hongmul, Akmal, Muhammad, Ryu, Ho Jin
Publikováno v:
In Journal of Materials Science & Technology 10 December 2024 202:240-252
Autor:
Kim, Minjae, Cho, JeongHyun, Tae Park, Kyung, Houn Rhee, Chang, Woong Park, Hai, Chul Jung, Ji
Publikováno v:
In Journal of Industrial and Engineering Chemistry 25 November 2024 139:250-257
We consider a stochastic fluid network where the external input processes are compound Poisson with heavy-tailed Weibullian jumps. Our results comprise of large deviations estimates for the buffer content process in the vector-valued Skorokhod space
Externí odkaz:
http://arxiv.org/abs/2202.12770
The empirical success of deep learning is often attributed to SGD's mysterious ability to avoid sharp local minima in the loss landscape, as sharp minima are known to lead to poor generalization. Recently, empirical evidence of heavy-tailed gradient
Externí odkaz:
http://arxiv.org/abs/2102.04297
Autor:
Cho, JeongHyun, Kim, Minjae, Yang, Inchan, Park, Kyung Tae, Rhee, Chang Houn, Park, Hai Woong, Jung, Ji Chul
Publikováno v:
In Journal of Rare Earths March 2024 42(3):506-514
For a class of additive processes driven by the affine recursion $X_{n+1} = A_n X_n + B_n$, we develop a sample-path large deviations principle in the $M_1'$ topology on $D [0,1]$. We allow $B_n$ to have both signs and focus on the case where Kesten'
Externí odkaz:
http://arxiv.org/abs/2010.10751
Autor:
Wang, Xingyu, Rhee, Chang-Han
In this paper we address the problem of rare-event simulation for heavy-tailed L\'evy processes with infinite activities. We propose a strongly efficient importance sampling algorithm that builds upon the sample path large deviations for heavy-tailed
Externí odkaz:
http://arxiv.org/abs/2007.08080