Search Results for author:
Found 1 papers, 0 papers with code
Dynamic Encoding and Decoding of Information for Split Learning in Mobile-Edge Computing: Leveraging Information Bottleneck Theory
Split learning is a privacy-preserving distributed learning paradigm in which an ML model (e. g., a neural network) is split into two parts (i. e., an encoder and a decoder).
Cannot find the paper you are looking for? You can
Submit a new open access paper.
