Yongdai Kim - RankMe

83 papers A* 14A 1B 1C 1Journal 65Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	Fair Model-based Clustering. AAAI Jinwon Park, Kunwoong Kim, Jihu Lee, Yongdai Kim
2026	J	`jnl`	Fair Model-based Clustering. CoRR Jinwon Park, Kunwoong Kim, Jihu Lee, Yongdai Kim
2025	J	`jnl`	Bayesian Additive Regression Trees for functional ANOVA model. CoRR Seokhun Park, Insung Kong, Yongdai Kim
2025	J	`jnl`	Bayesian Neural Networks for Functional ANOVA model. CoRR Seokhun Park, Choeun Kim, Jihu Lee, Yunseop Shin, Insung Kong, Yongdai Kim
2025	J	`jnl`	Doubly-Regressing Approach for Subgroup Fairness. CoRR Kyungseon Lee, Kunwoong Kim, Jihu Lee, Dongyoon Yang, Yongdai Kim
2025	J	`jnl`	Fair Bayesian Model-Based Clustering. CoRR Jihu Lee, Kunwoong Kim, Yongdai Kim
2025	A*	`conf`	Fair Clustering via Alignment. ICML Kunwoong Kim, Jihu Lee, Sangchul Park, Yongdai Kim
2025	J	`jnl`	Fair Clustering via Alignment. CoRR Kunwoong Kim, Jihu Lee, Sangchul Park, Yongdai Kim
2025	J	`jnl`	Fair Representation Learning for Continuous Sensitive Attributes Using Expectation of Integral Probability Metrics. IEEE Trans. Pattern Anal. Mach. Intell. Insung Kong, Kunwoong Kim, Yongdai Kim
2025	J	`jnl`	Fair Representation Learning for Continuous Sensitive Attributes using Expectation of Integral Probability Metrics. CoRR Insung Kong, Kunwoong Kim, Yongdai Kim
2025	J	`jnl`	Fairness Through Matching. CoRR Kunwoong Kim, Insung Kong, Jongjin Lee, Minwoo Chae, Sangchul Park, Yongdai Kim
2025	J	`jnl`	Fairness Through Matching. Trans. Mach. Learn. Res. Kunwoong Kim, Insung Kong, Jongjin Lee, Minwoo Chae, Sangchul Park, Yongdai Kim
2025	J	`jnl`	Knowledge Distillation of Uncertainty using Deep Latent Factor Model. CoRR Sehyun Park, Jongjin Lee, Yunseop Shin, Ilsang Ohn, Yongdai Kim
2025	J	`jnl`	Learning deep generative models based on binomial log-likelihood. Neurocomputing Hwichang Jeong, Insung Kong, Yongdai Kim
2025	J	`jnl`	Posterior Concentrations of Fully-Connected Bayesian Neural Networks with General Priors on the Weights. J. Mach. Learn. Res. Insung Kong, Yongdai Kim
2025	J	`jnl`	ReLU integral probability metric and its applications. CoRR Yuha Park, Kunwoong Kim, Insung Kong, Yongdai Kim
2025	A*	`conf`	TAROT: Towards Essentially Domain-Invariant Robustness with Theoretical Justification. CVPR Dongyoon Yang, Jihu Lee, Yongdai Kim
2025	J	`jnl`	TAROT: Towards Essentially Domain-Invariant Robustness with Theoretical Justification. CoRR Dongyoon Yang, Jihu Lee, Yongdai Kim
2025	A*	`conf`	Tensor Product Neural Networks for Functional ANOVA Model. ICML Seokhun Park, Insung Kong, Yongchan Choi, Chanmoo Park, Yongdai Kim
2025	J	`jnl`	Tensor Product Neural Networks for Functional ANOVA Model. CoRR Seokhun Park, Insung Kong, Yongchan Choi, Chanmoo Park, Yongdai Kim
2024	A*	`conf`	IOFM: Using the Interpolation Technique on the Over-Fitted Models to Identify Clean-Annotated Samples. AAAI Dongha Kim, Yongchan Choi, Kunwoong Kim, Ilsang Ohn, Yongdai Kim
2024	J	`jnl`	META-ANOVA: Screening interactions for interpretable machine learning. CoRR Yongchan Choi, Seokhun Park, Chanmoo Park, Dongha Kim, Yongdai Kim
2024	A*	`conf`	ODIM: Outlier Detection via Likelihood of Under-Fitted Generative Models. ICML Dongha Kim, Jaesung Hwang, Jongjin Lee, Kunwoong Kim, Yongdai Kim
2024	J	`jnl`	Posterior concentrations of fully-connected Bayesian neural networks with general priors on the weights. CoRR Insung Kong, Yongdai Kim
2023	J	`jnl`	A Bayesian sparse factor model with adaptive posterior concentration. CoRR Ilsang Ohn, Lizhen Lin, Yongdai Kim
2023	J	`jnl`	A Likelihood Approach to Nonparametric Estimation of a Singular Distribution Using Deep Generative Models. J. Mach. Learn. Res. Minwoo Chae, Dongha Kim, Yongdai Kim, Lizhen Lin
2023	A*	`conf`	Covariate balancing using the integral probability metric for causal inference. ICML Insung Kong, Yuha Park, Joonhyuk Jung, Kwonsang Lee, Yongdai Kim
2023	J	`jnl`	Covariate balancing using the integral probability metric for causal inference. CoRR Insung Kong, Yuha Park, Joonhyuk Jung, Kwonsang Lee, Yongdai Kim
2023	A*	`conf`	Enhancing Adversarial Robustness in Low-Label Regime via Adaptively Weighted Regularization and Knowledge Distillation. ICCV Dongyoon Yang, Insung Kong, Yongdai Kim
2023	J	`jnl`	Enhancing Adversarial Robustness in Low-Label Regime via Adaptively Weighted Regularization and Knowledge Distillation. CoRR Dongyoon Yang, Insung Kong, Yongdai Kim
2023	A*	`conf`	Improving Adversarial Robustness by Putting More Regularizations on Less Robust Samples. ICML Dongyoon Yang, Insung Kong, Yongdai Kim
2023	J	`jnl`	Improving Performance of Semi-Supervised Learning by Adversarial Attacks. CoRR Dongyoon Yang, Kunwoong Kim, Yongdai Kim
2023	A*	`conf`	Masked Bayesian Neural Networks : Theoretical Guarantee and its Posterior Inference. ICML Insung Kong, Dongyoon Yang, Jongjin Lee, Ilsang Ohn, Gyuseung Baek, Yongdai Kim
2023	J	`jnl`	Masked Bayesian Neural Networks : Theoretical Guarantee and its Posterior Inference. CoRR Insung Kong, Dongyoon Yang, Jongjin Lee, Ilsang Ohn, Gyuseung Baek, Yongdai Kim
2023	J	`jnl`	ODIM: an efficient method to detect outliers via inlier-memorization effect of deep generative models. CoRR Dongha Kim, Jaesung Hwang, Jongjin Lee, Kunwoong Kim, Yongdai Kim
2023	J	`jnl`	Online learning for the Dirichlet process mixture model via weakly conjugate approximation. Comput. Stat. Data Anal. Kuhwan Jeong, Minwoo Chae, Yongdai Kim
2023	J	`jnl`	Within-group fairness: A guidance for more sound between-group fairness. CoRR Sara Kim, Kyusang Yu, Yongdai Kim
2022	J	`jnl`	A modified least angle regression algorithm for interaction selection with heredity. Stat. Anal. Data Min. Woosung Kim, Seonghyeon Kim, Myung Hwan Na, Yongdai Kim
2022	J	`jnl`	Adaptive Regularization for Adversarial Training. CoRR Dongyoon Yang, Insung Kong, Yongdai Kim
2022	A*	`conf`	Learning fair representation with a parametric integral probability metric. ICML Dongha Kim, Kunwoong Kim, Insung Kong, Ilsang Ohn, Yongdai Kim
2022	J	`jnl`	Learning fair representation with a parametric integral probability metric. CoRR Dongha Kim, Kunwoong Kim, Insung Kong, Ilsang Ohn, Yongdai Kim
2022	J	`jnl`	Nonconvex Sparse Regularization for Deep Neural Networks and Its Optimality. Neural Comput. Ilsang Ohn, Yongdai Kim
2022	J	`jnl`	SLIDE: A surrogate fairness constraint to ensure fairness consistency. Neural Networks Kunwoong Kim, Ilsang Ohn, Sara Kim, Yongdai Kim
2022	J	`jnl`	SLIDE: a surrogate fairness constraint to ensure fairness consistency. CoRR Kunwoong Kim, Ilsang Ohn, Sara Kim, Yongdai Kim
2021	J	`jnl`	A likelihood approach to nonparametric estimation of a singular distribution using deep generative models. CoRR Minwoo Chae, Dongha Kim, Yongdai Kim, Lizhen Lin
2021	J	`jnl`	Fast convergence rates of deep neural networks for classification. Neural Networks Yongdai Kim, Ilsang Ohn, Dongha Kim
2021	J	`jnl`	INN: A Method Identifying Clean-annotated Samples via Consistency Effect in Deep Neural Networks. CoRR Dongha Kim, Yongchan Choi, Kunwoong Kim, Yongdai Kim
2021	A*	`conf`	Kernel-convoluted Deep Neural Networks with Data Augmentation. AAAI Minjin Kim, Young-geun Kim, Dongha Kim, Yongdai Kim, Myunghee Cho Paik
2021	J	`jnl`	Learning Multiple Quantiles With Neural Networks. J. Comput. Graph. Stat. Sang Jun Moon, Jong-June Jeon, Jason Sang Hun Lee, Yongdai Kim
2021	J	`jnl`	Understanding Effects of Architecture Design to Invariance and Complexity in Deep Neural Networks. IEEE Access Dongha Kim, Yongdai Kim
2020	J	`jnl`	Kernel-convoluted Deep Neural Networks with Data Augmentation. CoRR Minjin Kim, Young-geun Kim, Dongha Kim, Yongdai Kim, Myunghee Cho Paik
2020	J	`jnl`	Nonconvex sparse regularization for deep neural networks and its optimality. CoRR Ilsang Ohn, Yongdai Kim
2020	A	`conf`	On casting importance weighted autoencoder to an EM algorithm to learn deep generative models. AISTATS Dongha Kim, Jaesung Hwang, Yongdai Kim
2020	J	`jnl`	Primal path algorithm for compositional data analysis. Comput. Stat. Data Anal. Jong-June Jeon, Yongdai Kim, Sungho Won, Hosik Choi
2019	J	`jnl`	Can search engine data improve accuracy of demand forecasting for new products? Evidence from automotive market. Ind. Manag. Data Syst. Dongha Kim, JongRoul Woo, Jungwoo Shin, Jongsu Lee, Yongdai Kim
2019	J	`jnl`	Smooth Function Approximation by Deep Neural Networks with General Activation Functions. Entropy Ilsang Ohn, Yongdai Kim
2019	J	`jnl`	Smooth function approximation by deep neural networks with general activation functions. CoRR Ilsang Ohn, Yongdai Kim
2019	J	`jnl`	Understanding and Improving Virtual Adversarial Training. CoRR Dongha Kim, Yongchan Choi, Yongdai Kim
2018	J	`jnl`	Ensemble Method for Privacy-Preserving Logistic Regression Based on Homomorphic Encryption. IEEE Access Jung Hee Cheon, Duhyeong Kim, Yongdai Kim, Yongsoo Song
2018	J	`jnl`	Fast convergence rates of deep neural networks for classification. CoRR Yongdai Kim, Ilsang Ohn, Dongha Kim
2018	J	`jnl`	On variation of gradients of deep neural networks. CoRR Yongdai Kim, Dongha Kim
2018	J	`jnl`	Primal path algorithm for compositional data analysis. CoRR Jong-June Jeon, Yongdai Kim, Sungho Won, Hosik Choi
2017	J	`jnl`	A robust support vector machine for labeling errors. Commun. Stat. Simul. Comput. Hosik Choi, Yongdai Kim, Sunghoon Kwon, Changyi Park
2016	J	`jnl`	A modified local quadratic approximation algorithm for penalized optimization problems. Comput. Stat. Data Anal. Sangin Lee, Sunghoon Kwon, Yongdai Kim
2016	—	`conf`	An Online Gibbs Sampler Algorithm for Hierarchical Dirichlet Processes Prior. ECML/PKDD (1) Yongdai Kim, Minwoo Chae, Kuhwan Jeong, Byungyup Kang, Hyoju Chung
2016	J	`jnl`	Nonconvex penalized reduced rank regression and its oracle properties in high dimensions. J. Multivar. Anal. Heng Lian, Yongdai Kim
2015	C	`ed.`	Current Approaches in Applied Artificial Intelligence - 28th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2015, Seoul, South Korea, June 10-12, 2015, Proceedings IEA/AIE Moonis Ali, Young Sig Kwon, Chang-Hwan Lee, Juntae Kim, Yongdai Kim
2015	J	`jnl`	Moderately clipped LASSO. Comput. Stat. Data Anal. Sunghoon Kwon, Sangin Lee, Yongdai Kim
2013	J	`jnl`	An EM algorithm for the proportional hazards model with doubly censored data. Comput. Stat. Data Anal. Yongdai Kim, Joungyoun Kim, Woncheol Jang
2012	J	`jnl`	Consistent Model Selection Criteria on High Dimensions. J. Mach. Learn. Res. Yongdai Kim, Sunghoon Kwon, Hosik Choi
2011	J	`jnl`	Gene selection and prediction for cancer classification using support vector machines with a reject option. Comput. Stat. Data Anal. Hosik Choi, Donghwa Yeo, Sunghoon Kwon, Yongdai Kim
2011	J	`jnl`	Quadratic approximation on SCAD penalized estimation. Comput. Stat. Data Anal. Sunghoon Kwon, Hosik Choi, Yongdai Kim
2010	J	`jnl`	Asymptotic properties of the maximum likelihood estimator for the proportional hazards model with doubly censored data. J. Multivar. Anal. Yongdai Kim, Bumsoo Kim, Woncheol Jang
2009	J	`jnl`	Robust wavelet shrinkage using robust selection of thresholds. Stat. Comput. Hee-Seok Oh, Donghoh Kim, Yongdai Kim
2007	J	`jnl`	An empirical study on classification methods for alarms from a bug-finding static C analyzer. Inf. Process. Lett. Kwangkeun Yi, Hosik Choi, Jaehwang Kim, Yongdai Kim
2006	J	`jnl`	Intelligent storage: Cross-layer optimization for soft real-time workload. ACM Trans. Storage Youjip Won, Hyungkyu Chang, Jaemin Ryu, Yongdai Kim, Junseok Shim
2006	J	`jnl`	Maximum a posteriori pruning on decision trees and its application to bootstrap BUMPing. Comput. Stat. Data Anal. Jinseog Kim, Yongdai Kim
2006	J	`jnl`	Multiclass sparse logistic regression for classification of multiple cancer types using gene expression data. Comput. Stat. Data Anal. Yongdai Kim, Sunghoon Kwon, Seuck Heun Song
2004	J	`jnl`	A new algorithm to generate beta processes. Comput. Stat. Data Anal. Jaeyong Lee, Yongdai Kim
2004	J	`jnl`	Convex Hull Ensemble Machine for Regression and Classification. Knowl. Inf. Syst. Yongdai Kim, Jinseog Kim
2004	A*	`conf`	Gradient LASSO for feature selection. ICML Yongdai Kim, Jinseog Kim
2003	B	`conf`	Averaged Boosting: A Noise-Robust Ensemble Method. PAKDD Yongdai Kim
2002	A*	`conf`	Convex Hull Ensemble Machine. ICDM Yongdai Kim