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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 Integer partitions, q-series, and Modular forms file 서울과학기술 대학 김병찬
수학강연회 Infinite order rationally slice knots file 카이스트 수리과학과 박정환
수학강연회 Ill-posedness for incompressible Euler equations at critical regularit file 서울대학교 정인지
수학강연회 Idempotents and topologies file University of Waterloo Nico Spronk
수학강연회 Hybrid discontinuous Galerkin methods in computational science and engineering file 연세대 박은재
수학강연회 How to solve linear systems in practice file 이화여대 수학과 민조홍
수학강연회 High dimensional nonlinear dynamics file 경북대학교 도영해
수학강연회 Heavy-tailed large deviations and deep learning's generalization mystery file Northwestern University 이창한
특별강연 Harmonic bundles and Toda lattices with opposite sign file RIMS, Kyoto Univ. Takuro Mochizuki
수학강연회 Hamiltonian dynamics, Floer theory and symplectic topology file University of Wisconsin 오용근
수학강연회 Gromov-Witten-Floer theory and Lagrangian intersections in symplectic topology file IBS, 포항공과대학교 오용근
수학강연회 Green’s function for initial-boundary value problem file National Univ. of Singapore Shih-Hsien Yu
수학강연회 Global result for multiple positive radial solutions of p-Laplacian system on exterior domain file 부산대학교 이용훈
수학강연회 Geometry, algebra and computation in moduli theory file 서울대 현동훈
수학강연회 Geometric structures and representation spaces file 서울대학교 이계선
수학강연회 Geometric Langlands theory: A bridge between number theory and physics file 서울대학교 유필상
수학강연회 Generalized multiscale HDG (hybridizable discontinuous Galerkin) methods for flows in highly heterogeneous porous media file 육군사관학교 문미남
수학강연회 Gaussian free field and conformal field theory file 서울대학교 강남규
수학강연회 Freudenthal medal, Klein medal 수상자의 수학교육이론 file 서울대 수학교육과 권오남
수학강연회 Free boundary problems arising from mathematical finance file 경희대학교 전준기
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