Preprint
Dongha Kim, Yongchan Choi, Kunwoong Kim and Yongdai Kim (2021). INN: A stable method identifying clean-annotated samples via consistent effect in deep neural networks.
Ilsang Ohn, Seonghyun Kim, Seung Beom Seo, Young-Oh Kim and Yongdai Kim (2020). Model-wise uncertainty decomposition in multi-model ensemble hydrological projections.
Ilsang Ohn, Lizhen Lin and Yongdai Kim (2020). Adaptive Bayesian inference for high-dimensional factor models.
Jaesung Hwang, Jonngho Won, Seungju Han, Jae-Joon Han and Yongdai Kim (2020). Characterization of the solution set of generalized Lasso for rank-deficient design matrices.
Dongha Kim, Yongchan Choi and Yongdai Kim (2020) Understanding and Improving Deep Semi-Supervised Learning Methods.
Jong-Jung Jeon, Yongdai Kim and Dong-Ha Kim (2017). Rank-consistency of the generalized Bradley-Terry model with misspecified link.
Published Papers
2021 -
2015 - 2020
2010 - 2014
2000 - 2009
- 1999
Books
고학수, 김용대 외 5인 (2021). 인공지능 원론: 설명가능성을 중심으로. 박영사
김용대 (2021). 데이터과학자의 사고법, 김영사
김용대 외 (2020). 4차산업혁명과 미래사회 2, Edited by 연세대학교 경영연구소
이긍희, 김용대, 김기온 (2020). 딥러닝의 통계적 이해, 방송통신대학교
이동수, 권용만, 장인홍, 김세진, 김용대 (2018). R과 빅데이터 이해, 자유아카데미
Refereed Conference Talks
“Masked Bayesian Neural Networks : Theoretical Guarantee and its Posterior Inference” at ICML2023, Hawaii, July 2023.
“Improving adversarial robustness by putting more regularizations on less robust samples” at ICML2023, Hawaii, July 2023.
“Covariate balancing using the integral probability metric for causal inference” at ICML2023, Hawaii, July 2023.
“Convex Hull Ensemble Machine” at 2002 IEEE International Conference on Data Mining, Japan, December 2002.
“Learning fair representation with a parametric integral probability” at ICML 2022.
“Kernel-convoluted Deep Neural Networks with Data Augmentation” at The 35th AAAI 2021.
“On casting importance weighted auto-encoder to an EM algorithm to learn deep generative models” at AISTAT 2020, Italy.
“An Online Gibbs Sampler Algorithm for Hierarchical Dirichlet Processes Prior” at ECML-PKDD 2016, Italy, 2016/9/19~23.
“Gradient LASSO for feature selection” at ICML 2004.
“Averaged Boosting: A noise-robust ensemble method” at The Seventh Pacific-Asia Conference on Knowledge Discovery and Data Mining(PAKDD03), Seoul, 2003/4/28~2003/5/1.
“Convex Hull Ensemble Machine” at 2002 IEEE International Conference on Data Mining, Japan, December 2002.