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SKKU Researchers Develop Bayesian Method (j-LANCE) for Hidden Dependence Structures in High-Dimensional Data

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by Sungkyunkwan University

3d ago· 3 min readen

Summary

Professor Kyoungjae Lee of Sungkyunkwan University, along with researchers from Seoul National University and the University of Cincinnati, developed a Bayesian inference method called j-LANCE for detecting hidden dependence structures in multi-group high-dimensional data. The method simultaneously achieves theoretical guarantees and computational efficiency, addressing challenges in fields like genomics, climate science, finance, and sensor data analysis where numerous variables are observed simultaneously.

Key quotes

· 3 pulled
The research team of Professor Kyoungjae Lee of the Department of Statistics at Sungkyunkwan University, through joint research with Professor Won Chang of Seoul National University and Professor Xuan Cao of the University of Cincinnati, developed Bayesian inference for the hidden dependence structures of multi-group high-dimensional data.
In today's scientific and industrial fields, high-dimensional data in which numerous variables are observed simultaneously, such as genomic, climate, financial, and sensor data, are rapidly...
Achieving Theoretical guarantee and Computational Efficiency Simultaneously through the Development of j-LANCE, a Bayesian Joint Local Dependence Learning Method
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Achieving Theoretical guarantee and Computational Efficiency Simultaneously through the Development of j-LANCE, a Bayesian Joint Local Dependence Learning Method

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