Multi-Task Learning for Compositional Data via Sparse Network Lasso
Multi-task learning is a statistical methodology that aims to improve the generalization performances of estimation and prediction tasks by sharing common information among multiple tasks. On the other hand, compositional data consist of proportions as components summing to one. Because components o...
Main Authors: | Akira Okazaki, Shuichi Kawano |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-12-01
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Series: | Entropy |
Subjects: | |
Online Access: | https://www.mdpi.com/1099-4300/24/12/1839 |
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