We are experiencing minor difficulties with our submission forms, which we are working to resolve. If you have any issues while submitting items, please contact us at dspace-lib@mit.edu.

An Information-theoretic Approach to Unsupervised Feature Selection for High-Dimensional Data

Thumbnail Image
Download
Name

1910.03196.pdf

Description
Submitted version
Size

593.92 KB

Format

Adobe PDF

Checksum (MD5)

b31895b9fee23064889146c27b6bc75e

sword-2021-01-25T19:15:55.original.xml (130 B)
Original SWORD entry document
Author(s)
Huang, Shao-Lun
•
Xu, Xiangxiang
•
Zheng, Lizhong
Date Issued
2020
Journal
IEEE Journal on Selected Areas in Information Theory
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Version
Original manuscript
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/JSAIT.2020.2981538
PrivacyPermissionsAccessibilityContact us
Notify us about copyright concerns.