Application-driven Intersections between Information Theory and Machine Learning
Machine learning has been tremendously successful in the past decade. In this thesis, we introduce guidance and insights from information theory to practical machine learning algorithms. In particular, we study three application domains and demonstrate the algorithmic gain of integrating machine lea...
Main Author: | Liu, Litian |
---|---|
Other Authors: | Médard, Muriel |
Format: | Thesis |
Published: |
Massachusetts Institute of Technology
2022
|
Online Access: | https://hdl.handle.net/1721.1/139138 |
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