Noh, Yung-Kyun

17 publications

ICLR 2024 Kernel Metric Learning for In-Sample Off-Policy Evaluation of Deterministic RL Policies Haanvid Lee, Tri Wahyu Guntara, Jongmin Lee, Yung-Kyun Noh, Kee-Eung Kim

NeurIPS 2024 Maximum Entropy Inverse Reinforcement Learning of Diffusion Models with Energy-Based Models Sangwoong Yoon, Himchan Hwang, Dohyun Kwon, Yung-Kyun Noh, Frank C. Park

NeurIPS 2023 Energy-Based Models for Anomaly Detection: A Manifold Diffusion Recovery Approach Sangwoong Yoon, Young-Uk Jin, Yung-Kyun Noh, Frank Park

ICLR 2023 Geometrically Regularized Autoencoders for Non-Euclidean Data Cheongjae Jang, Yonghyeon Lee, Yung-Kyun Noh, Frank C. Park

NeurIPS 2023 Variational Weighting for Kernel Density Ratios Sangwoong Yoon, Frank Park, Gunsu Yun, Iljung Kim, Yung-Kyun Noh

NeurIPS 2022 A Reparametrization-Invariant Sharpness Measure Based on Information Geometry Cheongjae Jang, Sungyoon Lee, Frank Park, Yung-Kyun Noh

NeurIPS 2022 Local Metric Learning for Off-Policy Evaluation in Contextual Bandits with Continuous Actions Haanvid Lee, Jongmin Lee, Yunseon Choi, Wonseok Jeon, Byung-Jun Lee, Yung-Kyun Noh, Kee-Eung Kim

ICML 2021 Autoencoding Under Normalization Constraints Sangwoong Yoon, Yung-Kyun Noh, Frank Park

MLJ 2019 Foreword: Special Issue for the Journal Track of the 10th Asian Conference on Machine Learning (ACML 2018) Masashi Sugiyama, Yung-Kyun Noh

ICML 2018 K-Beam Minimax: Efficient Optimization for Deep Adversarial Learning Jihun Hamm, Yung-Kyun Noh

NeurIPS 2017 Generative Local Metric Learning for Kernel Regression Yung-Kyun Noh, Masashi Sugiyama, Kee-Eung Kim, Frank Park, Daniel D Lee

ACML 2017 Preface Min-Ling Zhang, Yung-Kyun Noh

AISTATS 2015 Direct Density-Derivative Estimation and Its Application in KL-Divergence Approximation Hiroaki Sasaki, Yung-Kyun Noh, Masashi Sugiyama

AAAI 2015 Reward Shaping for Model-Based Bayesian Reinforcement Learning Hyeoneun Kim, Woosang Lim, Kanghoon Lee, Yung-Kyun Noh, Kee-Eung Kim

AISTATS 2014 Bias Reduction and Metric Learning for Nearest-Neighbor Estimation of Kullback-Leibler Divergence Yung-Kyun Noh, Masashi Sugiyama, Song Liu, Marthinus Christoffel du Plessis, Frank Chongwoo Park, Daniel D. Lee

NeurIPS 2012 Diffusion Decision Making for Adaptive K-Nearest Neighbor Classification Yung-kyun Noh, Frank Park, Daniel D. Lee

NeurIPS 2010 Generative Local Metric Learning for Nearest Neighbor Classification Yung-kyun Noh, Byoung-tak Zhang, Daniel D. Lee