[2023.06.12(Mon.)]Artificial Intelligence & AI Convergence Network Colloquium | |||||||||
작성자 | 김성민 | 분류 | 행사 | ||||||
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공지대상 |
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등록일 | 2023-06-02 | 마감일 | 2023-06-12 | 마감여부 | ![]() |
조회수 | 184 |
공지부서 | 소프트웨어융합대학교학팀 | ||||||||
< Artificial Intelligence & AI Convergence Network Colloquium >
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without training, a.k.a the existence of strong lottery tickets, the subnetworks that achieve good
performance without any weight update. Neural network pruning is considered the main
cornerstone of model compression for reducing the costs of computation and memory.
Unfortunately, pruning a generative model has not been extensively explored, and all existing
pruning algorithms suffer from excessive weight-training costs, performance degradation,
limited generalizability, or complicated training. To address these problems, we propose to find a
strong lottery ticket via moment-matching scores. Our experimental results show that the
discovered subnetwork can perform similarly or better than the trained dense model even when
only 10% of the weights remain. To the best of our knowledge, we are the first to show the
existence of strong lottery tickets in generative models and provide an algorithm to find it
stably.
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2019.12 - 2021.07 EPFL Postdoctoral researcher
2018.02 - 2019.12 NAVER Search&Clova AI research scientist
2018.02 KAIST 박사 바이오및뇌공학과 / 지도교수 예종철
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이전 | 제10회 소개딩(SW개발보안 경진대회) 개최 안내 |
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다음 | [2023.06.02(Fri)] AI Convergence Network Colloquium |