Feature Decoupled of Deep Mutual Information Maximization-Reference-Cited by-同舟云学术

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Feature Decoupled of Deep Mutual Information Maximization

Published:2023-12-14 Issue: Volume:33 Page:1-6
ISSN:
Container-title:2023 2nd International Conference on Automation, Robotics and Computer Engineering (ICARCE)
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Author:

He Xing¹,Peng Changgen²,Wang Lin³,Tan Weijie²,Wang Zifan⁴

Affiliation:

1. College of Computer Science and Technology, Guizhou University,State Key Laboratory of Public Big Data,Guiyang,China

2. Guizhou Big Data Academy, Guizhou University,Guiyang,China

3. Guizhou Minzu University,Guizhou Key Laboratory of Pattern Recognition and Intelligent System,Guiyang,China

4. Institute of Guizhou Aerospace Measuring and Testing Technology,Guiyang,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10492487/10492472/10492476.pdf?arnumber=10492476

Reference26 articles.

1. A fast, on-line algorithm for PCA and its convergence characteristics

2. A Global Geometric Framework for Nonlinear Dimensionality Reduction

3. Nonlinear Dimensionality Reduction by Locally Linear Embedding

4. Laplacian Eigenmaps for Dimensionality Reduction and Data Representation

5. Hessian eigenmaps: Locally linear embedding techniques for high-dimensional data

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