Gyemin Lee

发表

Wealth Networks with Sharing Earnings and Expanding Trade Volume

Gwangil Kim, Gyemin Lee, 2009 .

Creating Level Set Trees Using One-Class Support Vector Machines

Gyemin Lee, 2015 .

THE SOLUTION PATH FOR THE BALANCED 2 C-SVM

Gyemin Lee, 2006 .

Transfer Learning for Automatic Gating of Flow Cytometry Data

Gyemin Lee, 2011 .

Research and applications: Predicting complications of percutaneous coronary intervention using a novel support vector method

Zeeshan Syed, Gyemin Lee, Hitinder S. Gurm, 2013, J. Am. Medical Informatics Assoc..

Feature Alignment by Uncertainty and Self-Training for Source-Free Unsupervised Domain Adaptation

Gyemin Lee, Joonho Lee, 2022, ArXiv.

Degree and wealth distribution in a network induced by wealth

Gyemin Lee, Gwangil Kim, Gwang Il Kim, 2007 .

Hierarchical Clustering Using One-Class Support

Neil Y. Yen, Gyemin Lee, Vector Machines, 2015 .

Domain Generalization by Marginal Transfer Learning

Gilles Blanchard, Gyemin Lee, Clayton Scott, 2017, J. Mach. Learn. Res..

Generalizing from Several Related Classification Tasks to a New Unlabeled Sample

Gilles Blanchard, Gyemin Lee, Clayton Scott, 2011, NIPS.

Hierarchical Clustering Using One-Class Support Vector Machines

Gyemin Lee, Gyemin Lee, 2015, Symmetry.

Predicting Complications of Percutaneous Coronary Intervention Using a Novel Support Vector Method

Zeeshan Syed, Gyemin Lee, Hitinder S. Gurm, 2012, 2012 IEEE Second International Conference on Healthcare Informatics, Imaging and Systems Biology.

Machine learning for flow cytometry data analysis

Gyemin Lee, Clayton Scott, C. Scott, 2011 .

Nested Support Vector Machines

Gyemin Lee, Clayton Scott, C. Scott, 2008, IEEE Transactions on Signal Processing.

The One Class Support Vector Machine Solution Path

Gyemin Lee, Clayton Scott, C. Scott, 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.

Feature Alignment by Uncertainty and Self-Training for Source-Free Unsupervised Domain Adaptation

Gyemin Lee, Joonho Lee, 2022, Neural Networks.

Statistical file matching of flow cytometry data

William Finn, Gyemin Lee, Clayton Scott, 2010, J. Biomed. Informatics.

EM algorithms for multivariate Gaussian mixture models with truncated and censored data

Gyemin Lee, Clayton Scott, C. Scott, 2012, Comput. Stat. Data Anal..

Transfer Learning for Auto-gating of Flow Cytometry Data

Gyemin Lee, Clayton Scott, Lloyd Stoolman, 2011, ICML Unsupervised and Transfer Learning.

Semi-Supervised Novelty Detection

Gilles Blanchard, Gyemin Lee, Clayton Scott, 2010, J. Mach. Learn. Res..

Adapting Surgical Models to Individual Hospitals Using Transfer Learning

Zeeshan Syed, Gyemin Lee, Ilan Rubinfeld, 2012, 2012 IEEE 12th International Conference on Data Mining Workshops.

Improving surgical models through one/two class learning

Zeeshan Syed, Zahi N. Karam, Gyemin Lee, 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

THE GLOBAL FINANCIAL CRISIS AND TRANSMISSION CHANNELS: AN INTERNATIONAL NETWORK ANALYSIS

Dongkoo Chang, Gyemin Lee, Changmo Ahn, 2014 .

Optimization of the collimator mask for the rotational modulation collimator-based gamma-ray/neutron dual-particle imager

Gyemin Lee, S. Ye, Geehyun Kim, 2019, Current Applied Physics.

A Monte Carlo simulation study for the gamma-ray/neutron dual-particle imager using rotational modulation collimator (RMC)

Gyemin Lee, S. Ye, Geehyun Kim, 2018, Journal of radiological protection : official journal of the Society for Radiological Protection.

Radiation imaging with a rotational modulation collimator (RMC) coupled to a Cs2LiYCl6:Ce (CLYC) detector

Gyemin Lee, S. Ye, Geehyun Kim, 2016 .

Monte Carlo simulation of rotational modulation collimator (RMC) patterns for the gamma-ray/neutron dual-particle imager

Gyemin Lee, S. Ye, Geehyun Kim, 2015, 2015 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC).

Domain Generalization by Marginal Transfer Learning

G. Blanchard, C. Scott, Ü. Dogan, 2017, J. Mach. Learn. Res..

Virtual Coverage: A New Approach to Coverage-Based Software Reliability Engineering

Gyemin Lee, Joong-Yang Park, Gyemin Lee, 2013 .

Estimation of Coverage Growth Functions

Gyemin Lee, Joong-Yang Park, Seo Yeong Kim, 2011 .

Selection of a Predictive Coverage Growth Function

Gyemin Lee, Joong-Yang Park, Gyemin Lee, 2010 .

Generalizing from Several Related Classification Tasks to a New Unlabeled Sample

G. Blanchard, C. Scott, Gyemin Lee, 2011, NIPS.

Unsupervised Domain Adaptation Based on the Predictive Uncertainty of Models

Gyemin Lee, Joonho Lee, Joonho Lee, 2022, Neurocomputing.