An Efficient Approach to Informative Feature Extraction from Multimodal Data
Copyright © 2019, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. One primary focus in multimodal feature extraction is to find the representations of individual modalities that are maximally correlated. As a well-known measure of dependence, the Hirsc...
Main Authors: | Wang, Lichen (Author), Wu, Jiaxiang (Author), Huang, Shao-Lun (Author), Zheng, Lizhong (Author), Xu, Xiangxiang (Author), Zhang, Lin (Author), Huang, Junzhou (Author) |
---|---|
Format: | Article |
Language: | English |
Published: |
Association for the Advancement of Artificial Intelligence (AAAI),
2021-11-08T19:30:22Z.
|
Subjects: | |
Online Access: | Get fulltext |
Similar Items
-
An information-theoretic approach to unsupervised feature selection for high-dimensional data
by: Huang, Shao-Lun, et al.
Published: (2021) -
An efficient algorithm for information decomposition and extraction
by: Makur, Anuran, et al.
Published: (2018) -
An Information Theoretic Interpretation to Deep Neural Networks
by: Huang, Shao-Lun, et al.
Published: (2021) -
A Local Characterization for Wyner Common Information
by: Huang, Shao-Lun, et al.
Published: (2021) -
An Information Theoretic Interpretation to Deep Neural Networks
by: Xu, Xiangxiang, et al.
Published: (2022)