Tensor Quantization: High-Dimensional Data Compression
Author:
Affiliation:
1. Department of Applied Data Science, San Jose State University, San Jose, CA, USA
2. School of Electrical Engineering and Computer Science, Louisiana State University, Baton Rouge, LA, USA
Funder
Louisiana Board of Regents Research Competitiveness Subprogram
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Media Technology
Link
http://xplorestaging.ieee.org/ielx7/76/9849156/09687585.pdf?arnumber=9687585
Reference47 articles.
1. Flexible Lossy Compression for Selective Encrypted Image With Image Inpainting
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3. Further results on Moore–Penrose inverses of tensors with application to tensor nearness problems
4. Matrix output extension of the tensor network Kalman filter with an application in MIMO Volterra system identification
5. A Tensor Network Kalman filter with an application in recursive MIMO Volterra system identification
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