Professor Myunghee Cho Paik

Department of Statistics

Seoul National University

Teaching

Fall 2020 Deep Learning: statistical perspective

Spring 2021 Sequential Decision Making

Recent manuscripts

Valid oversampling schemes to handle imbalance published in the Pattern Recognition Letters, 2019

Uncertainty quantification using Bayesian neural networks in classification: Application to biomedical image segmentation published in the CSDA, 2020

Lipschitz continuous autoencoders in application to anomaly detection presented at AISTATS 2020

Contextual multi-armed bandit algorithm for semiparametric reward model presented at ICML 2019

Principled analytic classifier for positive-unlabeled learning via weighted integral probability metric published in the Machine Learning, 2020

Doubly Robust Lasso Bandit presented at NeurIPs 2019

Principled Learning Method for Wasserstein Distributionally Robust Optimization with Local Perturbations presented at ICML 2020

Kernel-convoluted Deep Neural Networks with Data Augmentation presented at AAAI 2021

Doubly Robust Thompson Sampling for linear payoffs presented at NeurIPs 2021 (Spotlight)