Charmgil Hong

According to our database, Charmgil Hong authored at least 16 papers between 2013 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Drug Induced Liver Injury Prediction with Injective Molecular Transformer.

Geonyeong Choi, Hyo Jung Cho, Soon Sun Kim, Ji Eun Han, Jae Youn Cheong, Charmgil Hong

Proceedings of the IEEE EMBS International Conference on Biomedical and Health Informatics, 2023

2021

Multi-Scale Label Relation Learning for Multi-Label Classification Using 1-Dimensional Convolutional Neural Networks.

Junhyung Kim, Byungyoon Park, Charmgil Hong

CoRR, 2021

2019

Identifying incidental findings from radiology reports of trauma patients: An evaluation of automated feature representation methods.

Gaurav Trivedi, Charmgil Hong, Esmaeel R. Dadashzadeh, Robert M. Handzel, Harry Hochheiser, Shyam Visweswaran

Int. J. Medical Informatics, 2019

2018

Multivariate Conditional Outlier Detection: Identifying Unusual Input-Output Associations in Data.

Charmgil Hong, Milos Hauskrecht

Proceedings of the Thirty-First International Florida Artificial Intelligence Research Society Conference, 2018

2017

Detection of Abnormal Input-Output Associations.

Charmgil Hong, Siqi Liu, Milos Hauskrecht

CoRR, 2017

2016

Outlier-based detection of unusual patient-management actions: An ICU study.

Milos Hauskrecht, Iyad Batal, Charmgil Hong, Quang Nguyen, Gregory F. Cooper, Shyam Visweswaran, Gilles Clermont

J. Biomed. Informatics, 2016

Detecting Unusual Input-Output Associations in Multivariate Conditional Data.

Charmgil Hong, Milos Hauskrecht

CoRR, 2016

Dealing with Class Imbalance using Thresholding.

Charmgil Hong, Rumi Ghosh, Soundar Srinivasan

CoRR, 2016

Multivariate Conditional Outlier Detection and Its Clinical Application.

Charmgil Hong, Milos Hauskrecht

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

MCODE: Multivariate Conditional Outlier Detection.

Charmgil Hong, Milos Hauskrecht

CoRR, 2015

A Generalized Mixture Framework for Multi-label Classification.

Charmgil Hong, Iyad Batal, Milos Hauskrecht

Proceedings of the 2015 SIAM International Conference on Data Mining, Vancouver, BC, Canada, April 30, 2015

Multivariate Conditional Anomaly Detection and Its Clinical Application.

Charmgil Hong, Milos Hauskrecht

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014

A Mixtures-of-Experts Framework for Multi-Label Classification.

Charmgil Hong, Iyad Batal, Milos Hauskrecht

CoRR, 2014

An Optimization-based Framework to Learn Conditional Random Fields for Multi-label Classification.

Mahdi Pakdaman Naeini, Iyad Batal, Zitao Liu, Charmgil Hong, Milos Hauskrecht

Proceedings of the 2014 SIAM International Conference on Data Mining, 2014

A Mixtures-of-Trees Framework for Multi-Label Classification.

Charmgil Hong, Iyad Batal, Milos Hauskrecht

Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management, 2014

2013

An efficient probabilistic framework for multi-dimensional classification.

Iyad Batal, Charmgil Hong, Milos Hauskrecht

Proceedings of the 22nd ACM International Conference on Information and Knowledge Management, 2013