Yung-Kyun Noh

Publication Activity (10 Years)

Years Active: 2008-2024
Publications (10 Years): 35

Top Topics

Reinforcement Learning

Nearest Neighbor

Mobile Platforms

Metric Learning

Top Venues

Publications

Sangwoong Yoon, Himchan Hwang, Dohyun Kwon, Yung-Kyun Noh, Frank C. Park
Maximum Entropy Inverse Reinforcement Learning of Diffusion Models with Energy-Based Models. CoRR (2024)
Haanvid Lee, Tri Wahyu Guntara, Jongmin Lee, Yung-Kyun Noh, Kee-Eung Kim
Kernel Metric Learning for In-Sample Off-Policy Evaluation of Deterministic RL Policies. CoRR (2024)
Haanvid Lee, Tri Wahyu Guntara, Jongmin Lee, Yung-Kyun Noh, Kee-Eung Kim
Kernel Metric Learning for In-Sample Off-Policy Evaluation of Deterministic RL Policies. ICLR (2024)
Sangwoong Yoon, Young-Uk Jin, Yung-Kyun Noh, Frank C. Park
Energy-Based Models for Anomaly Detection: A Manifold Diffusion Recovery Approach. NeurIPS (2023)
Jae-Won Lee, Jong-Hyun Won, Seonggwang Jeon, Yujin Choo, Yubin Yeon, Jin-Seon Oh, Minsoo Kim, Seonhwa Kim, InSuk Joung, Cheongjae Jang, Sung Jong Lee, Tae Hyun Kim, Kyong Hwan Jin, Giltae Song, Eun-Sol Kim, Jejoong Yoo, Eunok Paek, Yung-Kyun Noh, Keehyoung Joo
DeepFold: enhancing protein structure prediction through optimized loss functions, improved template features, and re-optimized energy function. Bioinform. 39 (12) (2023)
Sangwoong Yoon, Frank Chongwoo Park, Gunsu S. Yun, Iljung Kim, Yung-Kyun Noh
Variational Weighting for Kernel Density Ratios. CoRR (2023)
Sangwoong Yoon, Frank C. Park, Gunsu S. Yun, Iljung Kim, Yung-Kyun Noh
Variational Weighting for Kernel Density Ratios. NeurIPS (2023)
Cheongjae Jang, Yonghyeon Lee, Yung-Kyun Noh, Frank C. Park
Geometrically regularized autoencoders for non-Euclidean data. ICLR (2023)
Beom Woo Kang, Junho Wohn, Seongju Lee, Sunghyun Park, Yung-Kyun Noh, Yongjun Park
Synchronization-Aware NAS for an Efficient Collaborative Inference on Mobile Platforms. LCTES (2023)
Sangwoong Yoon, Dohyun Kwon, Himchan Hwang, Yung-Kyun Noh, Frank C. Park
Generalized Contrastive Divergence: Joint Training of Energy-Based Model and Diffusion Model through Inverse Reinforcement Learning. CoRR (2023)
Sangwoong Yoon, Young-Uk Jin, Yung-Kyun Noh, Frank C. Park
Energy-Based Models for Anomaly Detection: A Manifold Diffusion Recovery Approach. CoRR (2023)
Haanvid Lee, Jongmin Lee, Yunseon Choi, Wonseok Jeon, Byung-Jun Lee, Yung-Kyun Noh, Kee-Eung Kim
Local Metric Learning for Off-Policy Evaluation in Contextual Bandits with Continuous Actions. NeurIPS (2022)
J. Jon Ryu, Shouvik Ganguly, Younghan Kim, Yung-Kyun Noh, Daniel D. Lee
Nearest Neighbor Density Functional Estimation From Inverse Laplace Transform. IEEE Trans. Inf. Theory 68 (6) (2022)
Haanvid Lee, Jongmin Lee, Yunseon Choi, Wonseok Jeon, Byung-Jun Lee, Yung-Kyun Noh, Kee-Eung Kim
Local Metric Learning for Off-Policy Evaluation in Contextual Bandits with Continuous Actions. CoRR (2022)
Cheongjae Jang, Sungyoon Lee, Frank C. Park, Yung-Kyun Noh
A Reparametrization-Invariant Sharpness Measure Based on Information Geometry. NeurIPS (2022)
Sangwoong Yoon, Jinwon Choi, Yonghyeon Lee, Yung-Kyun Noh, Frank Chongwoo Park
Evaluating Out-of-Distribution Detectors Through Adversarial Generation of Outliers. CoRR (2022)
Cheongjae Jang, Sang-Kyun Ko, Yung-Kyun Noh, Jieun Choi, Jongwon Lim, Tae-Jeong Kim
Learning to increase matching efficiency in identifying additional b-jets in the tt̅b̅ process. CoRR (2021)
Sangseon Lee, Taeheon Lee, Yung-Kyun Noh, Sun Kim
Ranked k-Spectrum Kernel for Comparative and Evolutionary Comparison of Exons, Introns, and CpG Islands. IEEE ACM Trans. Comput. Biol. Bioinform. 18 (3) (2021)
Cheongjae Jang, Yung-Kyun Noh, Frank Chongwoo Park
A Riemannian geometric framework for manifold learning of non-Euclidean data. Adv. Data Anal. Classif. 15 (3) (2021)
Sangwoong Yoon, Yung-Kyun Noh, Frank Chongwoo Park
Autoencoding Under Normalization Constraints. CoRR (2021)
Sangwoong Yoon, Yung-Kyun Noh, Frank Chongwoo Park
Autoencoding Under Normalization Constraints. ICML (2021)
Seunghyeon Kim, Yung-Kyun Noh, Frank C. Park
Efficient neural network compression via transfer learning for machine vision inspection. Neurocomputing 413 (2020)
Yung-Kyun Noh, Ji Young Park, Byoung Geol Choi, Kee-Eung Kim, Seung-Woon Rha
A Machine Learning-Based Approach for the Prediction of Acute Coronary Syndrome Requiring Revascularization. J. Medical Syst. 43 (8) (2019)
Masashi Sugiyama, Yung-Kyun Noh
Foreword: special issue for the journal track of the 10th Asian Conference on Machine Learning (ACML 2018). Mach. Learn. 108 (5) (2019)
Jiwon Hong, Sung-Jun Park, Taeri Kim, Yung-Kyun Noh, Sang-Wook Kim, Dongphil Kim, Wonho Kim
Malware classification for identifying author groups: a graph-based approach. RACS (2019)
Yung-Kyun Noh, Masashi Sugiyama, Song Liu, Marthinus Christoffel du Plessis, Frank Chongwoo Park, Daniel D. Lee
Bias Reduction and Metric Learning for Nearest-Neighbor Estimation of Kullback-Leibler Divergence. Neural Comput. 30 (7) (2018)
Jihun Hamm, Yung-Kyun Noh
K-Beam Minimax: Efficient Optimization for Deep Adversarial Learning. ICML (2018)
Yung-Kyun Noh, Byoung-Tak Zhang, Daniel D. Lee
Generative Local Metric Learning for Nearest Neighbor Classification. IEEE Trans. Pattern Anal. Mach. Intell. 40 (1) (2018)
Jihun Hamm, Yung-Kyun Noh
K-Beam Subgradient Descent for Minimax Optimization. CoRR (2018)
Shouvik Ganguly, Jongha Ryu, Young-Han Kim, Yung-Kyun Noh, Daniel D. Lee
Nearest neighbor density functional estimation based on inverse Laplace transform. CoRR (2018)
Yung-Kyun Noh, Jihun Hamm, Frank Chongwoo Park, Byoung-Tak Zhang, Daniel D. Lee
Fluid Dynamic Models for Bhattacharyya-Based Discriminant Analysis. IEEE Trans. Pattern Anal. Mach. Intell. 40 (1) (2018)
Seunghyeon Kim, Wooyoung Kim, Yung-Kyun Noh, Frank Chongwoo Park
Transfer learning for automated optical inspection. IJCNN (2017)
Hyoin Kim, Hyeonbeom Lee, Seungwon Choi, Yung-Kyun Noh, H. Jin Kim
Motion planning with movement primitives for cooperative aerial transportation in obstacle environment. ICRA (2017)
Yung-Kyun Noh, Masashi Sugiyama, Kee-Eung Kim, Frank C. Park, Daniel D. Lee
Generative Local Metric Learning for Kernel Regression. NIPS (2017)
Hiroaki Sasaki, Yung-Kyun Noh, Gang Niu, Masashi Sugiyama
Direct Density Derivative Estimation. Neural Comput. 28 (6) (2016)
Yung-Kyun Noh, Daniel D. Lee, Kyung-Ae Yang, Cheongtag Kim, Byoung-Tak Zhang
Molecular learning with DNA kernel machines. Biosyst. 137 (2015)
Hiroaki Sasaki, Yung-Kyun Noh, Masashi Sugiyama
Direct Density-Derivative Estimation and Its Application in KL-Divergence Approximation. AISTATS (2015)
Hyeoneun Kim, Woosang Lim, Kanghoon Lee, Yung-Kyun Noh, Kee-Eung Kim
Reward Shaping for Model-Based Bayesian Reinforcement Learning. AAAI (2015)
Yung-Kyun Noh, Masashi Sugiyama, Song Liu, Marthinus Christoffel du Plessis, Frank Chongwoo Park, Daniel D. Lee
Bias Reduction and Metric Learning for Nearest-Neighbor Estimation of Kullback-Leibler Divergence. AISTATS (2014)
Yung-Kyun Noh, Byoung-Kyong Min
Feature selection for brain-computer interface using nearest neighbor information. BCI (2014)
Yung-Kyun Noh, Frank Chongwoo Park, Daniel D. Lee
k-Nearest Neighbor Classification Algorithm for Multiple Choice Sequential Sampling. CogSci (2013)
Yung-Kyun Noh, Frank Chongwoo Park, Daniel D. Lee
Diffusion Decision Making for Adaptive k-Nearest Neighbor Classification. NIPS (2012)
Yuan Shi, Yung-Kyun Noh, Fei Sha, Daniel D. Lee
Learning Discriminative Metrics via Generative Models and Kernel Learning CoRR (2011)
Yung-Kyun Noh, Byoung-Tak Zhang, Daniel D. Lee
Fluid Dynamics Models for Low Rank Discriminant Analysis. AISTATS (2010)
Yung-Kyun Noh, Byoung-Tak Zhang, Daniel D. Lee
Generative Local Metric Learning for Nearest Neighbor Classification. NIPS (2010)
Yung-Kyun Noh, Jihun Ham, Daniel D. Lee
Regularized discriminant analysis for transformation-invariant object recognition. ICPR (2008)
Joon Shik Kim, Ji-Woo Lee, Yung-Kyun Noh, Ji-Yoon Park, Dong-Yoon Lee, Kyung-Ae Yang, Young-Gyu Chai, Jong Chan Kim, Byoung-Tak Zhang
An evolutionary Monte Carlo algorithm for predicting DNA hybridization. Biosyst. 91 (1) (2008)