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文献记录(part108)--Distributionally Robust and Multi-Objective Nonnegative Matrix Factorization
2022-07-21 17:41:00 【GoatGui】
学习笔记,仅供参考,有错必纠
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Distributionally Robust and Multi-Objective Nonnegative Matrix Factorization
Author:Nicolas Gillis, Le Thi Khanh Hien, Valentin Leplat , and Vincent Y. F. Tan
Journal:IEEE Transactions on Pattern Analysis and Machine Intelligence
Year:2022
DOI:10.1109/TPAMI.2021.3058693
Keywords:Nonnegative matrix factorization, multiple objectives, distributional robustness, multiplicative updates
Code:None
Abstract
非负矩阵分解 (NMF) 是一种用于分析非负数据的线性降维技术. NMF 的关键是目标函数的选择,该目标函数取决于对数据假设的噪声模型(or statistics of the noise). 在许多应用中,噪声模型是未知且难以估计的. 在本文中,我们定义了一个多目标 NMF (MO-NMF) 问题,其中多个目标组
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