J
Junghye Lee
Researcher at Ulsan National Institute of Science and Technology
Publications - 34
Citations - 446
Junghye Lee is an academic researcher from Ulsan National Institute of Science and Technology. The author has contributed to research in topics: Feature selection & Computer science. The author has an hindex of 8, co-authored 27 publications receiving 225 citations. Previous affiliations of Junghye Lee include Pohang University of Science and Technology.
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Privacy-Preserving Patient Similarity Learning in a Federated Environment: Development and Analysis.
TL;DR: The proposed algorithm can help search similar patients across institutions effectively to support federated data analysis in a privacy-preserving manner and confirmed privacy preservation in similarity search by using homomorphic encryption.
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Word2vec-based latent semantic analysis (W2V-LSA) for topic modeling: A study on blockchain technology trend analysis
TL;DR: A new topic modeling method called W2V-LSA, which is based on Word2vec and Spherical k-means clustering to better capture and represent the context of a corpus, which can be a competitive alternative for better topic modeling to provide direction for future research in technology trend analysis.
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Secure and Differentially Private Logistic Regression for Horizontally Distributed Data
TL;DR: A novel strategy that combines differential privacy methods and homomorphic encryption techniques to achieve the best of both worlds is introduced and demonstrated the practicability of building secure and privacy-preserving models with high efficiency and good accuracy using a few real-world datasets.
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An efficient multivariate feature ranking method for gene selection in high-dimensional microarray data
TL;DR: Classification of microarray data plays a significant role in the diagnosis and prediction of cancer, however, its high-dimensionality compared to the number of observations is questioned.
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Convolutional Neural Network-Based Land Cover Classification Using 2-D Spectral Reflectance Curve Graphs With Multitemporal Satellite Imagery
Miae Kim,Junghee Lee,Daehyeon Han,Minso Shin,Jungho Im,Junghye Lee,Lindi J. Quackenbush,Zhu Gu +7 more
TL;DR: This study shows that the use of a new transformation of spectral bands into a 2-D form for application in CNNs can improve land cover classification performance.