We stand with Ukraine

We stand with Ukraine

Myunghee Cho Paik

Orcid: 0000-0001-6239-4883

According to our database¹, Myunghee Cho Paik authored at least 25 papers between 2012 and 2024.

Collaborative distances:

Dijkstra number² of five.
Erdős number³ of four.

Timeline

Legend:

Book

In proceedings

Article

PhD thesis

Dataset

Other

Links

On csauthors.net:

Bibliography

2024

Doubly-Robust Off-Policy Evaluation with Estimated Logging Policy.

[BibT_eX]

[DOI]

,

Myunghee Cho Paik

CoRR, 2024

Mixed-Effects Contextual Bandits.

[BibT_eX]

[DOI]

,

Myunghee Cho Paik

,

,

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Semi-parametric contextual bandits with graph-Laplacian regularization.

[BibT_eX]

[DOI]

Young-Geun Choi

,

,

,

Myunghee Cho Paik

Inf. Sci., October, 2023

Conditional Wasserstein Generator.

[BibT_eX]

[DOI]

,

,

Myunghee Cho Paik

IEEE Trans. Pattern Anal. Mach. Intell., June, 2023

Wasserstein Geodesic Generator for Conditional Distributions.

[BibT_eX]

[DOI]

,

,

,

,

Myunghee Cho Paik

CoRR, 2023

Semi-Parametric Contextual Pricing Algorithm using Cox Proportional Hazards Model.

[BibT_eX]

[DOI]

Young-Geun Choi

,

,

,

,

Myunghee Cho Paik

,

Proceedings of the International Conference on Machine Learning, 2023

Squeeze All: Novel Estimator and Self-Normalized Bound for Linear Contextual Bandits.

[BibT_eX]

[DOI]

,

Myunghee Cho Paik

,

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Bandit-supported care planning for older people with complex health and care needs.

[BibT_eX]

[DOI]

,

,

,

Myunghee Cho Paik

,

Proceedings of the 5th IEEE International Conference on Artificial Intelligence Circuits and Systems, 2023

Double Doubly Robust Thompson Sampling for Generalized Linear Contextual Bandits.

[BibT_eX]

[DOI]

,

,

Myunghee Cho Paik

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2021

Doubly Robust Thompson Sampling with Linear Payoffs.

[BibT_eX]

[DOI]

,

,

Myunghee Cho Paik

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Kernel-convoluted Deep Neural Networks with Data Augmentation.

[BibT_eX]

[DOI]

,

,

,

,

Myunghee Cho Paik

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Principled analytic classifier for positive-unlabeled learning via weighted integral probability metric.

[BibT_eX]

[DOI]

,

,

Masashi Sugiyama

,

Myunghee Cho Paik

Mach. Learn., 2020

Uncertainty quantification using Bayesian neural networks in classification: Application to biomedical image segmentation.

[BibT_eX]

[DOI]

,

,

,

Myunghee Cho Paik

Comput. Stat. Data Anal., 2020

Principled learning method for Wasserstein distributionally robust optimization with local perturbations.

[BibT_eX]

[DOI]

,

,

,

Myunghee Cho Paik

Proceedings of the 37th International Conference on Machine Learning, 2020

Lipschitz Continuous Autoencoders in Application to Anomaly Detection.

[BibT_eX]

[DOI]

,

,

Hyunwoong Chang

,

Myunghee Cho Paik

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Valid oversampling schemes to handle imbalance.

[BibT_eX]

[DOI]

,

,

Myunghee Cho Paik

Pattern Recognit. Lett., 2019

An analytic formulation for positive-unlabeled learning via weighted integral probability metric.

[BibT_eX]

[DOI]

,

,

Masashi Sugiyama

,

Myunghee Cho Paik

CoRR, 2019

Doubly-Robust Lasso Bandit.

[BibT_eX]

[DOI]

,

Myunghee Cho Paik

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Contextual Multi-armed Bandit Algorithm for Semiparametric Reward Model.

[BibT_eX]

[DOI]

,

Myunghee Cho Paik

Proceedings of the 36th International Conference on Machine Learning, 2019

2017

Generalized estimating equations with stabilized working correlation structure.

[BibT_eX]

[DOI]

,

Young-Geun Choi

,

,

Andreas Ziegler

,

Myunghee Cho Paik

Comput. Stat. Data Anal., 2017

Causal inference with observational data under cluster-specific non-ignorable assignment mechanism.

[BibT_eX]

[DOI]

,

Myunghee Cho Paik

,

Comput. Stat. Data Anal., 2017

2016

Using link-preserving imputation for logistic partially linear models with missing covariates.

[BibT_eX]

[DOI]

,

Myunghee Cho Paik

,

,

Comput. Stat. Data Anal., 2016

Ensemble of Deep Convolutional Neural Networks for Prognosis of Ischemic Stroke.

[BibT_eX]

[DOI]

,

,

,

,

Myunghee Cho Paik

,

Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2016

2013

Robust inference using hierarchical likelihood approach for heavy-tailed longitudinal outcomes with missing data: An alternative to inverse probability weighted generalized estimating equations.

[BibT_eX]

[DOI]

,

,

Myunghee Cho Paik

,

Michael G. Kenward

Comput. Stat. Data Anal., 2013

2012

Semiparametric model for the dichotomized functional outcome after stroke: The Northern Manhattan Study.

[BibT_eX]

[DOI]

,

Myunghee Cho Paik

,

Mandip S. Dhamoon

,

Yeseon Park Moon

,

,

,

Mitchell S. V. Elkind

Comput. Stat. Data Anal., 2012

Loading...