Advancing deep active learning & data subset selection: unifying principles with information-theory intuitions
<p>At its core, this thesis aims to enhance the practicality of deep learning by improving the label and training efficiency of deep learning models. To this end, we investigate data subset selection techniques, specifically active learning and active sampling, grounded in information-theoreti...
Main Author: | Kirsch, A |
---|---|
Other Authors: | Gal, Y |
Format: | Thesis |
Language: | English |
Published: |
2023
|
Subjects: |
Similar Items
-
Structure and uncertainty in deep learning
by: Smith, L
Published: (2022) -
Understanding uncertainty in deep learning builds confidence
by: Jürgen Bajorath
Published: (2022-12-01) -
Deep Learning Applications /
by: Mazzeo, Pier Luigi, editor, et al.
Published: (2021) -
Towards unified visual perception
by: Sun, S
Published: (2024) -
Integrated Modeling of Hybrid Nanofiltration/Reverse Osmosis Desalination Plant Using Deep Learning-Based Crow Search Optimization Algorithm
by: Sani. I. Abba, et al.
Published: (2023-10-01)