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강연자 이창한
소속 Northwestern University
date 2021-09-16

 

Abstract: 
While the typical behaviors of stochastic systems are often deceptively oblivious to the tail distributions of the underlying uncertainties, the ways rare events arise are vastly different depending on whether the underlying tail distributions are light-tailed or heavy-tailed. Roughly speaking, in light-tailed settings, a system-wide rare event arises because everything goes wrong a little bit as if the entire system has conspired up to provoke the rare event (conspiracy principle), whereas, in heavy-tailed settings, a system-wide rare event arises because a small number of components fail catastrophically (catastrophe principle). In the first part of this talk, I will introduce the recent developments in the theory of large deviations for heavy-tailed stochastic processes at the sample path level and rigorously characterize the catastrophe principle. In the second part, I will explore an intriguing connection between the catastrophe principle and a central mystery of modern AI—the unreasonably good generalization performance of deep neural networks.
 
This talk is based on the ongoing research in collaboration with Mihail Bazhba, Jose Blanchet, Bohan Chen, Sewoong Oh, Insuk Seo, Zhe Su, Xingyu Wang, and Bert Zwart.
 
Short Bio: 
Chang-Han Rhee is an Assistant Professor in Industrial Engineering and Management Sciences at Northwestern University. Before joining Northwestern University, he was a postdoctoral researcher in the Stochastics Group at Centrum Wiskunde & Informatica and in Industrial & Systems Engineering and Biomedical Engineering at Georgia Tech. He received his Ph.D. in Computational and Mathematical Engineering from Stanford University. His research interests include applied probability, stochastic simulation, and statistical learning. He was a winner of the Outstanding Publication Award from the INFORMS Simulation Society in 2016, a winner of the Best Student Paper Award (MS/OR focused) at the 2012 Winter Simulation Conference, and a finalist of the 2013 INFORMS George Nicholson Student Paper Competition.
Atachment
첨부 '1'
List of Articles
카테고리 제목 소속 강연자
수학강연회 Root multiplicities of hyperbolic Kac-Moody algebras and Fourier coefficients of modular forms file Univ. of Connecticut 이규환
BK21 FOUR Rookies Pitch 2022-1 Rookies Pitch: Cryptography (이기우) file 수리과학부 이기우
수학강연회 학부학생을 위한 강연회: 기하학과 우주론 file 홍익대학교 이남훈
BK21 FOUR Rookies Pitch 2021-1 Rookies Pitch: Optimization Theory (이다빈) file IBS-DIMAG 이다빈
BK21 FOUR Rookies Pitch 2021-2 Rookies Pitch: Low Demensional Topology (이동수) file QSMS 이동수
수학강연회 Trends to equilibrium in collisional rarefied gas theory file 포항공과대학교 이동현
수학강연회 Mirror symmetry of pairings file 숭실대학교 이상욱
BK21 FOUR Rookies Pitch 2023-1 Symplectic Topology (이상진) file IBS-CGP 이상진
수학강연회 <학부생을 위한 ɛ 강연> Convergence of Fourier series and integrals in Lebesgue spaces file 서울대 이상혁
Maximal averages in harmonic analysis file 서울대학교 이상혁
BK21 FOUR Rookies Pitch 2022-1 Rookies Pitch: Number Theory (이석형) file QSMS 이석형
BK21 FOUR Rookies Pitch 2023-1 Dynamics and Number Theory (이슬비) file IBS-CGP 이슬비
BK21 FOUR Rookies Pitch 2021-1 Rookies Pitch: Algebraic Combinatorics(이승재), Algebraic Geometry(조창연) file 이승재(기초과학연구원), 조창연(QSMS)
수학강연회 An introduction to hyperplane arrangements file 서울대 이승진
수학강연회 Creation of concepts for prediction models and quantitative trading file Haafor 이승환
BK21 FOUR Rookies Pitch 2022-2 Rookies Pitch: Representation Theory(이신명) file 수리과학부 이신명
수학강연회 On function field and smooth specialization of a hypersurface in the projective space file KAIST 이용남
수학강연회 Global result for multiple positive radial solutions of p-Laplacian system on exterior domain file 부산대학교 이용훈
수학강연회 <정년퇴임 기념강연> Hardy, Beurling, and invariant subspaces file 서울대학교 이우영
BK21 FOUR Rookies Pitch 2023-1 Stochastic PDE(이재윤) file KIAS 이재윤
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