Yongdai Kim

Publication Activity (10 Years)

Years Active: 2002-2024
Publications (10 Years): 46

Top Topics

Nonparametric Estimation

Generative Model

Covariate Shift

Top Venues

Comput. Stat. Data Anal.

Stat. Anal. Data Min.

Publications

Insung Kong, Yongdai Kim
Posterior concentrations of fully-connected Bayesian neural networks with general priors on the weights. CoRR (2024)
Dongha Kim, Yongchan Choi, Kunwoong Kim, Ilsang Ohn, Yongdai Kim
IOFM: Using the Interpolation Technique on the Over-Fitted Models to Identify Clean-Annotated Samples. AAAI (2024)
Minwoo Chae, Dongha Kim, Yongdai Kim, Lizhen Lin
A Likelihood Approach to Nonparametric Estimation of a Singular Distribution Using Deep Generative Models. J. Mach. Learn. Res. 24 (2023)
Dongyoon Yang, Insung Kong, Yongdai Kim
Enhancing Adversarial Robustness in Low-Label Regime via Adaptively Weighted Regularization and Knowledge Distillation. CoRR (2023)
Insung Kong, Dongyoon Yang, Jongjin Lee, Ilsang Ohn, Gyuseung Baek, Yongdai Kim
Masked Bayesian Neural Networks : Theoretical Guarantee and its Posterior Inference. ICML (2023)
Kuhwan Jeong, Minwoo Chae, Yongdai Kim
Online learning for the Dirichlet process mixture model via weakly conjugate approximation. Comput. Stat. Data Anal. 179 (2023)
Dongha Kim, Jaesung Hwang, Jongjin Lee, Kunwoong Kim, Yongdai Kim
ODIM: an efficient method to detect outliers via inlier-memorization effect of deep generative models. CoRR (2023)
Insung Kong, Dongyoon Yang, Jongjin Lee, Ilsang Ohn, Gyuseung Baek, Yongdai Kim
Masked Bayesian Neural Networks : Theoretical Guarantee and its Posterior Inference. CoRR (2023)
Dongyoon Yang, Insung Kong, Yongdai Kim
Enhancing Adversarial Robustness in Low-Label Regime via Adaptively Weighted Regularization and Knowledge Distillation. ICCV (2023)
Insung Kong, Yuha Park, Joonhyuk Jung, Kwonsang Lee, Yongdai Kim
Covariate balancing using the integral probability metric for causal inference. CoRR (2023)
Insung Kong, Yuha Park, Joonhyuk Jung, Kwonsang Lee, Yongdai Kim
Covariate balancing using the integral probability metric for causal inference. ICML (2023)
Sara Kim, Kyusang Yu, Yongdai Kim
Within-group fairness: A guidance for more sound between-group fairness. CoRR (2023)
Dongyoon Yang, Kunwoong Kim, Yongdai Kim
Improving Performance of Semi-Supervised Learning by Adversarial Attacks. CoRR (2023)
Dongyoon Yang, Insung Kong, Yongdai Kim
Improving Adversarial Robustness by Putting More Regularizations on Less Robust Samples. ICML (2023)
Seonghyeon Kim, Sara Kim, Kunwoong Kim, Yongdai Kim
regularization for fair artificial intelligence robust to covariate shift. Stat. Anal. Data Min. 16 (3) (2023)
Ilsang Ohn, Lizhen Lin, Yongdai Kim
A Bayesian sparse factor model with adaptive posterior concentration. CoRR (2023)
Insung Kong, Dongyoon Yang, Jongjin Lee, Ilsang Ohn, Yongdai Kim
Masked Bayesian Neural Networks : Computation and Optimality. CoRR (2022)
Woosung Kim, Seonghyeon Kim, Myung Hwan Na, Yongdai Kim
A modified least angle regression algorithm for interaction selection with heredity. Stat. Anal. Data Min. 15 (5) (2022)
Dongha Kim, Kunwoong Kim, Insung Kong, Ilsang Ohn, Yongdai Kim
Learning fair representation with a parametric integral probability metric. CoRR (2022)
Ilsang Ohn, Yongdai Kim
Nonconvex Sparse Regularization for Deep Neural Networks and Its Optimality. Neural Comput. 34 (2) (2022)
Kunwoong Kim, Ilsang Ohn, Sara Kim, Yongdai Kim
SLIDE: a surrogate fairness constraint to ensure fairness consistency. CoRR (2022)
Dongyoon Yang, Insung Kong, Yongdai Kim
Adaptive Regularization for Adversarial Training. CoRR (2022)
Kunwoong Kim, Ilsang Ohn, Sara Kim, Yongdai Kim
SLIDE: A surrogate fairness constraint to ensure fairness consistency. Neural Networks 154 (2022)
Dongha Kim, Kunwoong Kim, Insung Kong, Ilsang Ohn, Yongdai Kim
Learning fair representation with a parametric integral probability metric. ICML (2022)
Minwoo Chae, Dongha Kim, Yongdai Kim, Lizhen Lin
A likelihood approach to nonparametric estimation of a singular distribution using deep generative models. CoRR (2021)
Dongha Kim, Yongdai Kim
Understanding Effects of Architecture Design to Invariance and Complexity in Deep Neural Networks. IEEE Access 9 (2021)
Yongdai Kim, Ilsang Ohn, Dongha Kim
Fast convergence rates of deep neural networks for classification. Neural Networks 138 (2021)
Minjin Kim, Young-geun Kim, Dongha Kim, Yongdai Kim, Myunghee Cho Paik
Kernel-convoluted Deep Neural Networks with Data Augmentation. AAAI (2021)
Dongha Kim, Yongchan Choi, Kunwoong Kim, Yongdai Kim
INN: A Method Identifying Clean-annotated Samples via Consistency Effect in Deep Neural Networks. CoRR (2021)
Sang Jun Moon, Jong-June Jeon, Jason Sang Hun Lee, Yongdai Kim
Learning Multiple Quantiles With Neural Networks. J. Comput. Graph. Stat. 30 (4) (2021)
Dongha Kim, Jaesung Hwang, Yongdai Kim
On casting importance weighted autoencoder to an EM algorithm to learn deep generative models. AISTATS (2020)
Minjin Kim, Young-geun Kim, Dongha Kim, Yongdai Kim, Myunghee Cho Paik
Kernel-convoluted Deep Neural Networks with Data Augmentation. CoRR (2020)
Ilsang Ohn, Yongdai Kim
Nonconvex sparse regularization for deep neural networks and its optimality. CoRR (2020)
Jong-June Jeon, Yongdai Kim, Sungho Won, Hosik Choi
Primal path algorithm for compositional data analysis. Comput. Stat. Data Anal. 148 (2020)
Dongha Kim, JongRoul Woo, Jungwoo Shin, Jongsu Lee, Yongdai Kim
Can search engine data improve accuracy of demand forecasting for new products? Evidence from automotive market. Ind. Manag. Data Syst. 119 (5) (2019)
Ilsang Ohn, Yongdai Kim
Smooth function approximation by deep neural networks with general activation functions. CoRR (2019)
Ilsang Ohn, Yongdai Kim
Smooth Function Approximation by Deep Neural Networks with General Activation Functions. Entropy 21 (7) (2019)
Dongha Kim, Yongchan Choi, Yongdai Kim
Understanding and Improving Virtual Adversarial Training. CoRR (2019)
Yongdai Kim, Ilsang Ohn, Dongha Kim
Fast convergence rates of deep neural networks for classification. CoRR (2018)
Jong-June Jeon, Yongdai Kim, Sungho Won, Hosik Choi
Primal path algorithm for compositional data analysis. CoRR (2018)
Jung Hee Cheon, Duhyeong Kim, Yongdai Kim, Yongsoo Song
Ensemble Method for Privacy-Preserving Logistic Regression Based on Homomorphic Encryption. IEEE Access 6 (2018)
Yongdai Kim, Dongha Kim
On variation of gradients of deep neural networks. CoRR (2018)
Hosik Choi, Yongdai Kim, Sunghoon Kwon, Changyi Park
A robust support vector machine for labeling errors. Commun. Stat. Simul. Comput. 46 (8) (2017)
Heng Lian, Yongdai Kim
Nonconvex penalized reduced rank regression and its oracle properties in high dimensions. J. Multivar. Anal. 143 (2016)
Yongdai Kim, Minwoo Chae, Kuhwan Jeong, Byungyup Kang, Hyoju Chung
An Online Gibbs Sampler Algorithm for Hierarchical Dirichlet Processes Prior. ECML/PKDD (1) (2016)
Sangin Lee, Sunghoon Kwon, Yongdai Kim
A modified local quadratic approximation algorithm for penalized optimization problems. Comput. Stat. Data Anal. 94 (2016)
Sunghoon Kwon, Sangin Lee, Yongdai Kim
Moderately clipped LASSO. Comput. Stat. Data Anal. 92 (2015)
Yongdai Kim, Joungyoun Kim, Woncheol Jang
An EM algorithm for the proportional hazards model with doubly censored data. Comput. Stat. Data Anal. 57 (1) (2013)
Yongdai Kim, Sunghoon Kwon, Hosik Choi
Consistent Model Selection Criteria on High Dimensions. J. Mach. Learn. Res. 13 (2012)
Sunghoon Kwon, Hosik Choi, Yongdai Kim
Quadratic approximation on SCAD penalized estimation. Comput. Stat. Data Anal. 55 (1) (2011)
Hosik Choi, Donghwa Yeo, Sunghoon Kwon, Yongdai Kim
Gene selection and prediction for cancer classification using support vector machines with a reject option. Comput. Stat. Data Anal. 55 (5) (2011)
Yongdai Kim, Bumsoo Kim, Woncheol Jang
Asymptotic properties of the maximum likelihood estimator for the proportional hazards model with doubly censored data. J. Multivar. Anal. 101 (6) (2010)
Hee-Seok Oh, Donghoh Kim, Yongdai Kim
Robust wavelet shrinkage using robust selection of thresholds. Stat. Comput. 19 (1) (2009)
Kwangkeun Yi, Hosik Choi, Jaehwang Kim, Yongdai Kim
An empirical study on classification methods for alarms from a bug-finding static C analyzer. Inf. Process. Lett. 102 (2-3) (2007)
Youjip Won, Hyungkyu Chang, Jaemin Ryu, Yongdai Kim, Junseok Shim
Intelligent storage: Cross-layer optimization for soft real-time workload. ACM Trans. Storage 2 (3) (2006)
Yongdai Kim, Sunghoon Kwon, Seuck Heun Song
Multiclass sparse logistic regression for classification of multiple cancer types using gene expression data. Comput. Stat. Data Anal. 51 (3) (2006)
Jinseog Kim, Yongdai Kim
Maximum a posteriori pruning on decision trees and its application to bootstrap BUMPing. Comput. Stat. Data Anal. 50 (3) (2006)
Jaeyong Lee, Yongdai Kim
A new algorithm to generate beta processes. Comput. Stat. Data Anal. 47 (3) (2004)
Yongdai Kim, Jinseog Kim
Convex Hull Ensemble Machine for Regression and Classification. Knowl. Inf. Syst. 6 (6) (2004)
Yongdai Kim, Jinseog Kim
Gradient LASSO for feature selection. ICML (2004)
Yongdai Kim
Averaged Boosting: A Noise-Robust Ensemble Method. PAKDD (2003)
Yongdai Kim
Convex Hull Ensemble Machine. ICDM (2002)