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Myunghee Cho Paik
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2020 – today
- 2024
- [c12]Kyungbok Lee
, Myunghee Cho Paik, Min-hwan Oh, Gi-Soo Kim:
Mixed-Effects Contextual Bandits. AAAI 2024: 13409-13417 - [i12]Kyungbok Lee, Myunghee Cho Paik:
Doubly-Robust Off-Policy Evaluation with Estimated Logging Policy. CoRR abs/2404.01830 (2024) - 2023
- [j10]Young-Geun Choi
Semi-parametric contextual bandits with graph-Laplacian regularization. Inf. Sci. 645: 119367 (2023) - [j9]Young-geun Kim
Conditional Wasserstein Generator. IEEE Trans. Pattern Anal. Mach. Intell. 45(6): 7208-7219 (2023) - [c11]Wonyoung Kim, Kyungbok Lee, Myunghee Cho Paik:
Double Doubly Robust Thompson Sampling for Generalized Linear Contextual Bandits. AAAI 2023: 8300-8307 - [c10]Gi-Soo Kim, Young Suh Hong, Tae Hoon Lee, Myunghee Cho Paik, Hongsoo Kim:
Bandit-supported care planning for older people with complex health and care needs. AICAS 2023: 1-5 - [c9]Wonyoung Kim, Myunghee Cho Paik, Min-hwan Oh:
Squeeze All: Novel Estimator and Self-Normalized Bound for Linear Contextual Bandits. AISTATS 2023: 3098-3124 - [c8]Young-Geun Choi, Gi-Soo Kim, Yunseo Choi, Wooseong Cho, Myunghee Cho Paik, Min-hwan Oh:
Semi-Parametric Contextual Pricing Algorithm using Cox Proportional Hazards Model. ICML 2023: 5771-5786 - [i11]Gi-Soo Kim, Young Suh Hong, Tae Hoon Lee, Myunghee Cho Paik, Hongsoo Kim:
Bandit-supported care planning for older people with complex health and care needs. CoRR abs/2303.07053 (2023) - [i10]Young-geun Kim, Kyungbok Lee, Youngwon Choi, Joong-Ho Won, Myunghee Cho Paik:
Wasserstein Geodesic Generator for Conditional Distributions. CoRR abs/2308.10145 (2023) - 2022
- [i9]Young-Geun Choi, Gi-Soo Kim, Seunghoon Paik, Myunghee Cho Paik:
Semi-Parametric Contextual Bandits with Graph-Laplacian Regularization. CoRR abs/2205.08295 (2022) - [i8]Wonyoung Kim, Min-hwan Oh, Myunghee Cho Paik:
Squeeze All: Novel Estimator and Self-Normalized Bound for Linear Contextual Bandits. CoRR abs/2206.05404 (2022) - [i7]Wonyoung Kim, Kyungbok Lee, Myunghee Cho Paik:
Double Doubly Robust Thompson Sampling for Generalized Linear Contextual Bandits. CoRR abs/2209.06983 (2022) - 2021
- [c7]Minjin Kim, Young-geun Kim, Dongha Kim, Yongdai Kim, Myunghee Cho Paik:
Kernel-convoluted Deep Neural Networks with Data Augmentation. AAAI 2021: 8155-8162 - [c6]Wonyoung Kim, Gi-Soo Kim, Myunghee Cho Paik:
Doubly Robust Thompson Sampling with Linear Payoffs. NeurIPS 2021: 15830-15840 - [i6]Wonyoung Kim, Gi-Soo Kim, Myunghee Cho Paik:
Doubly Robust Thompson Sampling for linear payoffs. CoRR abs/2102.01229 (2021) - 2020
- [j8]Yongchan Kwon, Joong-Ho Won, Beomjoon Kim
Uncertainty quantification using Bayesian neural networks in classification: Application to biomedical image segmentation. Comput. Stat. Data Anal. 142 (2020) - [j7]Yongchan Kwon, Wonyoung Kim, Masashi Sugiyama
Principled analytic classifier for positive-unlabeled learning via weighted integral probability metric. Mach. Learn. 109(3): 513-532 (2020) - [c5]Young-geun Kim, Yongchan Kwon, Hyunwoong Chang, Myunghee Cho Paik:
Lipschitz Continuous Autoencoders in Application to Anomaly Detection. AISTATS 2020: 2507-2517 - [c4]Yongchan Kwon, Wonyoung Kim, Joong-Ho Won, Myunghee Cho Paik:
Principled learning method for Wasserstein distributionally robust optimization with local perturbations. ICML 2020: 5567-5576 - [i5]Yongchan Kwon, Wonyoung Kim, Joong-Ho Won, Myunghee Cho Paik:
Principled Learning Method for Wasserstein distributionally robust optimization with local perturbations. CoRR abs/2006.03333 (2020) - [i4]Minjin Kim, Young-geun Kim, Dongha Kim, Yongdai Kim, Myunghee Cho Paik:
Kernel-convoluted Deep Neural Networks with Data Augmentation. CoRR abs/2012.02521 (2020)
2010 – 2019
- 2019
- [j6]Young-geun Kim
Valid oversampling schemes to handle imbalance. Pattern Recognit. Lett. 125: 661-667 (2019) - [c3]Gi-Soo Kim, Myunghee Cho Paik:
Contextual Multi-armed Bandit Algorithm for Semiparametric Reward Model. ICML 2019: 3389-3397 - [c2]Gi-Soo Kim, Myunghee Cho Paik:
Doubly-Robust Lasso Bandit. NeurIPS 2019: 5869-5879 - [i3]Yongchan Kwon, Wonyoung Kim, Masashi Sugiyama, Myunghee Cho Paik:
An analytic formulation for positive-unlabeled learning via weighted integral probability metric. CoRR abs/1901.09503 (2019) - [i2]Gi-Soo Kim, Myunghee Cho Paik:
Contextual Multi-armed Bandit Algorithm for Semiparametric Reward Model. CoRR abs/1901.11221 (2019) - [i1]Gi-Soo Kim, Myunghee Cho Paik:
Doubly-Robust Lasso Bandit. CoRR abs/1907.11362 (2019) - 2017
- [j5]Yongchan Kwon, Young-Geun Choi, Taesung Park, Andreas Ziegler, Myunghee Cho Paik
Generalized estimating equations with stabilized working correlation structure. Comput. Stat. Data Anal. 106: 1-11 (2017) - [j4]Gi-Soo Kim, Myunghee Cho Paik
Causal inference with observational data under cluster-specific non-ignorable assignment mechanism. Comput. Stat. Data Anal. 113: 88-99 (2017) - 2016
- [j3]Qixuan Chen, Myunghee Cho Paik
Using link-preserving imputation for logistic partially linear models with missing covariates. Comput. Stat. Data Anal. 101: 174-185 (2016) - [c1]Youngwon Choi
Ensemble of Deep Convolutional Neural Networks for Prognosis of Ischemic Stroke. BrainLes@MICCAI 2016: 231-243 - 2013
- [j2]Donghwan Lee
Robust inference using hierarchical likelihood approach for heavy-tailed longitudinal outcomes with missing data: An alternative to inverse probability weighted generalized estimating equations. Comput. Stat. Data Anal. 59: 171-179 (2013) - 2012
- [j1]Huaihou Chen
Semiparametric model for the dichotomized functional outcome after stroke: The Northern Manhattan Study. Comput. Stat. Data Anal. 56(8): 2598-2608 (2012)
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last updated on 2024-10-01 21:37 CEST by the dblp team
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