A Value Theory of Meta-Learning Algorithms
Abstract
We use game theory to analyze meta-learning algorithms. The objective of meta-learning is to determine which algorithm to apply on a given task. This is an instance of a more general problem that consists of allocating knowledge consumers to learning producers. Solving this general problem in the field of meta-learning yields solutions for related fields such as information retrieval and recommender systems.
Cite
Text
Bagherjeiran. "A Value Theory of Meta-Learning Algorithms." AAAI Conference on Artificial Intelligence, 2006.Markdown
[Bagherjeiran. "A Value Theory of Meta-Learning Algorithms." AAAI Conference on Artificial Intelligence, 2006.](https://mlanthology.org/aaai/2006/bagherjeiran2006aaai-value/)BibTeX
@inproceedings{bagherjeiran2006aaai-value,
title = {{A Value Theory of Meta-Learning Algorithms}},
author = {Bagherjeiran, Abraham},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2006},
pages = {1904-1905},
url = {https://mlanthology.org/aaai/2006/bagherjeiran2006aaai-value/}
}