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2020 – today
- 2024
[j15]Young Woong Park
, Jinhak Kim, Dan Zhu:
Discordance minimization-based imputation algorithms for missing values in rating data. Mach. Learn. 113(1): 241-279 (2024)- [j14]Yeasung Jeong, Kangbok Lee, Young Woong Park, Sumin Han:
A systematic approach for learning imbalanced data: enhancing zero-inflated models through boosting. Mach. Learn. 113(10): 8233-8299 (2024) - [j13]Kangbok Lee, Sumin Han, Hyeoncheol Baik, Yeasung Jeong, Young Woong Park:
Observation weights matching approach for causal inference. Pattern Recognit. 154: 110549 (2024) - [c3]Jiana Meng, Young Woong Park, Chen Zhang:
Joint Effects and Sequencing of Government Regulations in Sharing Economy Era. AMCIS 2024 - 2023
- [c2]Yeasung Jeong, Kang-Bok Lee, Sumin Han, Young Woong Park, Junyoung Park:
CIO Turnover and its Consequences for Competitors. AMCIS 2023 - [i5]Young Woong Park, Jinhak Kim, Dan Zhu:
Discordance Minimization-based Imputation Algorithms for Missing Values in Rating Data. CoRR abs/2311.04035 (2023) - 2022
- [j12]Young Woong Park, Jennifer Blackhurst, Chinju Paul, Kevin P. Scheibe:
An analysis of the ripple effect for disruptions occurring in circular flows of a supply chain network. Int. J. Prod. Res. 60(15): 4693-4711 (2022) - 2021
- [j11]Jinhak Kim, Young Woong Park, Alvin J. Williams:
A Mathematical Programming Approach for Imputation of Unknown Journal Ratings in a Combined Journal Quality List. Decis. Sci. 52(2): 455-482 (2021) - [j10]Young Woong Park:
Optimization for L1-Norm Error Fitting via Data Aggregation. INFORMS J. Comput. 33(1): 120-142 (2021) - 2020
- [j9]Young Woong Park:
MILP Models for Complex System Reliability Redundancy Allocation with Mixed Components. INFORMS J. Comput. 32(3): 600-619 (2020) - [j8]Young Woong Park, Diego Klabjan:
Subset selection for multiple linear regression via optimization. J. Glob. Optim. 77(3): 543-574 (2020) - [j7]Seokhyun Chung, Young Woong Park, Taesu Cheong:
A mathematical programming approach for integrated multiple linear regression subset selection and validation. Pattern Recognit. 108: 107565 (2020)
2010 – 2019
- 2018
- [j6]Young Woong Park, Diego Klabjan:
Three iteratively reweighted least squares algorithms for L1 -norm principal component analysis. Knowl. Inf. Syst. 54(3): 541-565 (2018) - 2017
- [j5]Young Woong Park, Yan Jiang, Diego Klabjan, Loren Williams:
Algorithms for Generalized Clusterwise Linear Regression. INFORMS J. Comput. 29(2): 301-317 (2017) - [j4]Young Woong Park, Diego Klabjan:
Bayesian Network Learning via Topological Order. J. Mach. Learn. Res. 18: 99:1-99:32 (2017) - [i4]Young Woong Park, Diego Klabjan:
Bayesian Network Learning via Topological Order. CoRR abs/1701.05654 (2017) - 2016
- [j3]Young Woong Park, Diego Klabjan:
An aggregate and iterative disaggregate algorithm with proven optimality in machine learning. Mach. Learn. 105(2): 199-232 (2016) - [c1]Young Woong Park, Diego Klabjan:
Iteratively Reweighted Least Squares Algorithms for L1-Norm Principal Component Analysis. ICDM 2016: 430-438 - [i3]Young Woong Park, Diego Klabjan:
An Aggregate and Iterative Disaggregate Algorithm with Proven Optimality in Machine Learning. CoRR abs/1607.01400 (2016) - [i2]Young Woong Park, Yan Jiang, Diego Klabjan, Loren Williams:
Algorithms for Generalized Cluster-wise Linear Regression. CoRR abs/1607.01417 (2016) - [i1]Young Woong Park, Diego Klabjan:
Iteratively Reweighted Least Squares Algorithms for L1-Norm Principal Component Analysis. CoRR abs/1609.02997 (2016) - 2015
- [j2]Young Woong Park, Diego Klabjan:
Lot sizing with minimum order quantity. Discret. Appl. Math. 181: 235-254 (2015) - [j1]Sergey Shebalov, Young Woong Park, Diego Klabjan:
Lifting for mixed integer programs with variable upper bounds. Discret. Appl. Math. 186: 226-250 (2015)
Coauthor Index
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