Education


Ph.D. Student in School of Computing, KAIST, South Korea (Present),
Advisor: Sung Ju Hwang

Received M.S. in Computer Engineering, UNIST, South Korea (Feb. 2018),
Advisor: Sung Ju Hwang
Received B.S. in Computer Engineering, UNIST, South Korea (Aug. 2016)

Experience


Research Intern @AItrics, South Korea (Mar. 2018 - May. 2018)
Contract Research Scientist @MLAI LAB (Machine Learning and Artificial Intelligence LAB) at KAIST, South Korea (Feb. 2018 - Aug. 2018)

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Email: jaehong.yoon at kaist dot ac dot kr
Github: jaehong-yoon93
CV: cv_jhyoon(pdf)

Research Interests

Machine Learning, Deep Learning, with special focus on scalable / efficient models and algorithms, network structure estimation, lifelong-able (online) continual learning, and biologically plausible neural networks.

Publications & Preprints


"Scalable and Order-robust Continual Learning with Additive Parameter Decomposition"
Jaehong Yoon, Saehoon Kim, Eunho Yang and Sung Ju Hwang, ICLR 2020, Addis Ababa

"Adaptive Network Sparsification via Dependent Variational Beta-Bernoulli Dropout"
Juho Lee, S. Kim, J. Yoon, H. B. Lee, E. Yang, S. J. Hwang, arXiv preprint arXiv:1805.10896 (2018)

"Lifelong Learning with Dynamically Expandable Networks"
Jaehong Yoon, Eunho Yang, Jeongtae Lee and Sung Ju Hwang, ICLR 2018, Vancouver

"Combined and Group and Exclusive Sparsity for Deep Neural Networks"
Jaehong Yoon, Sung Ju Hwang, ICML 2017, Sydney

Invited Talks

“Lifelong Learning with Dynamically Expandable Networks”

    Samsung SDS, Korea, Sep. 2019

    Tech. talk, NAVER corp., Korea, July. 2018

    Tech. Open Congress(T-T.O.C.), SK-Telecom, Korea, Mar. 2018

“Combined Group and Exclusive Sparsity for Deep Neural Networks”

    Korea Software Congress(KSC), Korea, Dec. 2017

Awards

NAVER Ph.D. Fellowship Award 2017

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