Yung-Kyun Noh - RankMe

51 papers A* 12A 3B 4C 1Journal 26Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	On the Information Processing of One-Dimensional Wasserstein Distances with Finite Samples. AAAI Cheongjae Jang, Jong-Hyun Won, Soyeon Jun, Chun Kee Chung, Keehyoung Joo, Yung-Kyun Noh
2025	J	`jnl`	On the Information Processing of One-Dimensional Wasserstein Distances with Finite Samples. CoRR Cheongjae Jang, Jong-Hyun Won, Soyeon Jun, Chun Kee Chung, Keehyoung Joo, Yung-Kyun Noh
2024	A*	`conf`	Kernel Metric Learning for In-Sample Off-Policy Evaluation of Deterministic RL Policies. ICLR Haanvid Lee, Tri Wahyu Guntara, Jongmin Lee, Yung-Kyun Noh, Kee-Eung Kim
2024	J	`jnl`	Kernel Metric Learning for In-Sample Off-Policy Evaluation of Deterministic RL Policies. CoRR Haanvid Lee, Tri Wahyu Guntara, Jongmin Lee, Yung-Kyun Noh, Kee-Eung Kim
2024	A*	`conf`	Maximum Entropy Inverse Reinforcement Learning of Diffusion Models with Energy-Based Models. NeurIPS Sangwoong Yoon, Himchan Hwang, Dohyun Kwon, Yung-Kyun Noh, Frank C. Park
2024	J	`jnl`	Maximum Entropy Inverse Reinforcement Learning of Diffusion Models with Energy-Based Models. CoRR Sangwoong Yoon, Himchan Hwang, Dohyun Kwon, Yung-Kyun Noh, Frank C. Park
2023	J	`jnl`	DeepFold: enhancing protein structure prediction through optimized loss functions, improved template features, and re-optimized energy function. Bioinform. 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
2023	A*	`conf`	Energy-Based Models for Anomaly Detection: A Manifold Diffusion Recovery Approach. NeurIPS Sangwoong Yoon, Young-Uk Jin, Yung-Kyun Noh, Frank C. Park
2023	J	`jnl`	Energy-Based Models for Anomaly Detection: A Manifold Diffusion Recovery Approach. CoRR Sangwoong Yoon, Young-Uk Jin, Yung-Kyun Noh, Frank C. Park
2023	J	`jnl`	Generalized Contrastive Divergence: Joint Training of Energy-Based Model and Diffusion Model through Inverse Reinforcement Learning. CoRR Sangwoong Yoon, Dohyun Kwon, Himchan Hwang, Yung-Kyun Noh, Frank C. Park
2023	A*	`conf`	Geometrically regularized autoencoders for non-Euclidean data. ICLR Cheongjae Jang, Yonghyeon Lee, Yung-Kyun Noh, Frank C. Park
2023	B	`conf`	Synchronization-Aware NAS for an Efficient Collaborative Inference on Mobile Platforms. LCTES Beom Woo Kang, Junho Wohn, Seongju Lee, Sunghyun Park, Yung-Kyun Noh, Yongjun Park
2023	A*	`conf`	Variational Weighting for Kernel Density Ratios. NeurIPS Sangwoong Yoon, Frank C. Park, Gunsu S. Yun, Iljung Kim, Yung-Kyun Noh
2023	J	`jnl`	Variational Weighting for Kernel Density Ratios. CoRR Sangwoong Yoon, Frank Chongwoo Park, Gunsu S. Yun, Iljung Kim, Yung-Kyun Noh
2022	A*	`conf`	A Reparametrization-Invariant Sharpness Measure Based on Information Geometry. NeurIPS Cheongjae Jang, Sungyoon Lee, Frank C. Park, Yung-Kyun Noh
2022	J	`jnl`	Evaluating Out-of-Distribution Detectors Through Adversarial Generation of Outliers. CoRR Sangwoong Yoon, Jinwon Choi, Yonghyeon Lee, Yung-Kyun Noh, Frank Chongwoo Park
2022	A*	`conf`	Local Metric Learning for Off-Policy Evaluation in Contextual Bandits with Continuous Actions. NeurIPS Haanvid Lee, Jongmin Lee, Yunseon Choi, Wonseok Jeon, Byung-Jun Lee, Yung-Kyun Noh, Kee-Eung Kim
2022	J	`jnl`	Local Metric Learning for Off-Policy Evaluation in Contextual Bandits with Continuous Actions. CoRR Haanvid Lee, Jongmin Lee, Yunseon Choi, Wonseok Jeon, Byung-Jun Lee, Yung-Kyun Noh, Kee-Eung Kim
2022	J	`jnl`	Nearest Neighbor Density Functional Estimation From Inverse Laplace Transform. IEEE Trans. Inf. Theory J. Jon Ryu, Shouvik Ganguly, Younghan Kim, Yung-Kyun Noh, Daniel D. Lee
2021	J	`jnl`	A Riemannian geometric framework for manifold learning of non-Euclidean data. Adv. Data Anal. Classif. Cheongjae Jang, Yung-Kyun Noh, Frank Chongwoo Park
2021	A*	`conf`	Autoencoding Under Normalization Constraints. ICML Sangwoong Yoon, Yung-Kyun Noh, Frank Chongwoo Park
2021	J	`jnl`	Autoencoding Under Normalization Constraints. CoRR Sangwoong Yoon, Yung-Kyun Noh, Frank Chongwoo Park
2021	J	`jnl`	Learning to increase matching efficiency in identifying additional b-jets in the tt̅b̅ process. CoRR Cheongjae Jang, Sang-Kyun Ko, Yung-Kyun Noh, Jieun Choi, Jongwon Lim, Tae-Jeong Kim
2021	J	`jnl`	Ranked k-Spectrum Kernel for Comparative and Evolutionary Comparison of Exons, Introns, and CpG Islands. IEEE ACM Trans. Comput. Biol. Bioinform. Sangseon Lee, Taeheon Lee, Yung-Kyun Noh, Sun Kim
2020	J	`jnl`	Efficient neural network compression via transfer learning for machine vision inspection. Neurocomputing Seunghyeon Kim, Yung-Kyun Noh, Frank C. Park
2019	J	`jnl`	A Machine Learning-Based Approach for the Prediction of Acute Coronary Syndrome Requiring Revascularization. J. Medical Syst. Yung-Kyun Noh, Ji Young Park, Byoung Geol Choi, Kee-Eung Kim, Seung-Woon Rha
2019	J	`jnl`	Foreword: special issue for the journal track of the 10th Asian Conference on Machine Learning (ACML 2018). Mach. Learn. Masashi Sugiyama, Yung-Kyun Noh
2019	—	`conf`	Malware classification for identifying author groups: a graph-based approach. RACS Jiwon Hong, Sung-Jun Park, Taeri Kim, Yung-Kyun Noh, Sang-Wook Kim, Dongphil Kim, Wonho Kim
2018	J	`jnl`	Bias Reduction and Metric Learning for Nearest-Neighbor Estimation of Kullback-Leibler Divergence. Neural Comput. Yung-Kyun Noh, Masashi Sugiyama, Song Liu, Marthinus Christoffel du Plessis, Frank Chongwoo Park, Daniel D. Lee
2018	J	`jnl`	Fluid Dynamic Models for Bhattacharyya-Based Discriminant Analysis. IEEE Trans. Pattern Anal. Mach. Intell. Yung-Kyun Noh, Jihun Hamm, Frank Chongwoo Park, Byoung-Tak Zhang, Daniel D. Lee
2018	J	`jnl`	Generative Local Metric Learning for Nearest Neighbor Classification. IEEE Trans. Pattern Anal. Mach. Intell. Yung-Kyun Noh, Byoung-Tak Zhang, Daniel D. Lee
2018	A*	`conf`	K-Beam Minimax: Efficient Optimization for Deep Adversarial Learning. ICML Jihun Hamm, Yung-Kyun Noh
2018	J	`jnl`	K-Beam Subgradient Descent for Minimax Optimization. CoRR Jihun Hamm, Yung-Kyun Noh
2018	J	`jnl`	Nearest neighbor density functional estimation based on inverse Laplace transform. CoRR Shouvik Ganguly, Jongha Ryu, Young-Han Kim, Yung-Kyun Noh, Daniel D. Lee
2017	—	`conf`	Generative Local Metric Learning for Kernel Regression. NIPS Yung-Kyun Noh, Masashi Sugiyama, Kee-Eung Kim, Frank C. Park, Daniel D. Lee
2017	A*	`conf`	Motion planning with movement primitives for cooperative aerial transportation in obstacle environment. ICRA Hyoin Kim, Hyeonbeom Lee, Seungwon Choi, Yung-Kyun Noh, H. Jin Kim
2017	C	`ed.`	Proceedings of The 9th Asian Conference on Machine Learning, ACML 2017, Seoul, Korea, November 15-17, 2017. ACML Min-Ling Zhang, Yung-Kyun Noh
2017	B	`conf`	Transfer learning for automated optical inspection. IJCNN Seunghyeon Kim, Wooyoung Kim, Yung-Kyun Noh, Frank Chongwoo Park
2016	J	`jnl`	Direct Density Derivative Estimation. Neural Comput. Hiroaki Sasaki, Yung-Kyun Noh, Gang Niu, Masashi Sugiyama
2015	A	`conf`	Direct Density-Derivative Estimation and Its Application in KL-Divergence Approximation. AISTATS Hiroaki Sasaki, Yung-Kyun Noh, Masashi Sugiyama
2015	J	`jnl`	Molecular learning with DNA kernel machines. Biosyst. Yung-Kyun Noh, Daniel D. Lee, Kyung-Ae Yang, Cheong-Tag Kim, Byoung-Tak Zhang
2015	A*	`conf`	Reward Shaping for Model-Based Bayesian Reinforcement Learning. AAAI Hyeoneun Kim, Woosang Lim, Kanghoon Lee, Yung-Kyun Noh, Kee-Eung Kim
2014	A	`conf`	Bias Reduction and Metric Learning for Nearest-Neighbor Estimation of Kullback-Leibler Divergence. AISTATS Yung-Kyun Noh, Masashi Sugiyama, Song Liu, Marthinus Christoffel du Plessis, Frank Chongwoo Park, Daniel D. Lee
2014	—	`conf`	Feature selection for brain-computer interface using nearest neighbor information. BCI Yung-Kyun Noh, Byoung-Kyong Min
2013	B	`conf`	k-Nearest Neighbor Classification Algorithm for Multiple Choice Sequential Sampling. CogSci Yung-Kyun Noh, Frank Chongwoo Park, Daniel D. Lee
2012	—	`conf`	Diffusion Decision Making for Adaptive k-Nearest Neighbor Classification. NIPS Yung-Kyun Noh, Frank Chongwoo Park, Daniel D. Lee
2011	J	`jnl`	Learning Discriminative Metrics via Generative Models and Kernel Learning CoRR Yuan Shi, Yung-Kyun Noh, Fei Sha, Daniel D. Lee
2010	A	`conf`	Fluid Dynamics Models for Low Rank Discriminant Analysis. AISTATS Yung-Kyun Noh, Byoung-Tak Zhang, Daniel D. Lee
2010	—	`conf`	Generative Local Metric Learning for Nearest Neighbor Classification. NIPS Yung-Kyun Noh, Byoung-Tak Zhang, Daniel D. Lee
2008	J	`jnl`	An evolutionary Monte Carlo algorithm for predicting DNA hybridization. Biosyst. 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
2008	B	`conf`	Regularized discriminant analysis for transformation-invariant object recognition. ICPR Yung-Kyun Noh, Jihun Ham, Daniel D. Lee