Yung-Kyun Noh

发表

Direct Density-Derivative Estimation and Its Application in KL-Divergence Approximation

Masashi Sugiyama, Hiroaki Sasaki, Yung-Kyun Noh, 2014, AISTATS.

Generative Local Metric Learning for Kernel Regression

Kee-Eung Kim, Frank Chongwoo Park, Masashi Sugiyama, 2017, NIPS.

Transfer learning for automated optical inspection

Frank C. Park, Yung-Kyun Noh, Seunghyeon Kim, 2017, 2017 International Joint Conference on Neural Networks (IJCNN).

Nearest neighbor density functional estimation based on inverse Laplace transform pdf

Daniel D. Lee, Young-Han Kim, Yung-Kyun Noh, 2018, ArXiv.

Malware classification for identifying author groups: a graph-based approach

Jiwon Hong, Sung-Jun Park, Sang-Wook Kim, 2019, RACS.

Model Dependency of the Performance in Generative Local Metric Learning

Frank C. Park, Yung-Kyun Noh, Daniel D. Lee, 2011 .

Generative Local Metric Learning for Nearest Neighbor Classification

Byoung-Tak Zhang, Daniel D. Lee, Yung-Kyun Noh, 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Regularized discriminant analysis for transformation-invariant object recognition

Daniel D. Lee, Jihun Ham, Yung-Kyun Noh, 2008, 2008 19th International Conference on Pattern Recognition.

Efﬁcient Neural Network Compression via Transfer Learning for Industrial Optical Inspection

Seunghyeon Kim, Frank C. Park, Yung-Kyun Noh, 2018 .

Diffusion Decision Making for Adaptive k-Nearest Neighbor Classification

Frank Chongwoo Park, Daniel D. Lee, Yung-Kyun Noh, 2012, NIPS.

Scalable Iterative Algorithm for Robust Subspace Clustering pdf

Jinwoo Shin, Yung-Kyun Noh, Sanghyuk Chun, 2015, ArXiv.

k-Nearest Neighbor Classification Algorithm for Multiple Choice Sequential Sampling

Frank Chongwoo Park, Daniel D. Lee, Yung-Kyun Noh, 2013, CogSci.

Direct Density Derivative Estimation

Gang Niu, Masashi Sugiyama, Hiroaki Sasaki, 2016, Neural Computation.

An evolutionary Monte Carlo algorithm for predicting DNA hybridization

Byoung-Tak Zhang, Dong-Yoon Lee, Yung-Kyun Noh, 2008, Biosyst..

Reward Shaping for Model-Based Bayesian Reinforcement Learning

Kee-Eung Kim, Yung-Kyun Noh, Kanghoon Lee, 2015, AAAI.

Efficient neural network compression via transfer learning for machine vision inspection

Yung-Kyun Noh, Seunghyeon Kim, Frank C. Park, 2020, Neurocomputing.

Learning Discriminative Metrics via Generative Models and Kernel Learning pdf

Daniel D. Lee, Yuan Shi, Fei Sha, 2011, ArXiv.

Molecular learning with DNA kernel machines

Byoung-Tak Zhang, Daniel D. Lee, Yung-Kyun Noh, 2015, Biosyst..

Bias Reduction and Metric Learning for Nearest-Neighbor Estimation of Kullback-Leibler Divergence

Frank Chongwoo Park, Masashi Sugiyama, Daniel D. Lee, 2018, Neural Computation.

Nearest neighbor density functional estimation from inverse Laplace transform

Daniel D. Lee, Yung-Kyun Noh, Young-Han Kim, 2018 .

K-Beam Minimax: Efficient Optimization for Deep Adversarial Learning

Jihun Hamm, Yung-Kyun Noh, Jihun Hamm, 2018, ICML.

Fluid Dynamics Models for Low Rank Discriminant Analysis

Byoung-Tak Zhang, Daniel D. Lee, Yung-Kyun Noh, 2010, AISTATS.

A Riemannian geometric framework for manifold learning of non-Euclidean data

Yung-Kyun Noh, Cheongjae Jang, Frank C. Park, 2020, Advances in Data Analysis and Classification.

Fluid Dynamic Models for Bhattacharyya-Based Discriminant Analysis

Byoung-Tak Zhang, Frank Chongwoo Park, Daniel D. Lee, 2018, IEEE Transactions on Pattern Analysis and Machine Intelligence.

K-Beam Subgradient Descent for Minimax Optimization pdf

Jihun Hamm, Yung-Kyun Noh, Jihun Hamm, 2018, ICML 2018.

Feature selection for brain-computer interface using nearest neighbor information

Byoung-Kyong Min, Yung-Kyun Noh, 2014, 2014 International Winter Workshop on Brain-Computer Interface (BCI).

Ranked k-Spectrum Kernel for Comparative and Evolutionary Comparison of Exons, Introns, and CpG Islands

Yung-Kyun Noh, Sangseon Lee, Sun Kim, 2019, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Autoencoding Under Normalization Constraints

Frank Chongwoo Park, Yung-Kyun Noh, Sangwoong Yoon, 2021, International Conference on Machine Learning.

Learning to increase matching efficiency in identifying additional b-jets in the $$\text {t}\bar{\text {t}}\text {b}\bar{\text {b}}$$ t

Department of Physics, Yung-Kyun Noh, Hanyang University, 2021, The European Physical Journal Plus.