Structured Weight-Based Prediction Algorithms
Abstract
Reviewing structured weight-based prediction algorithms (SWP for short) due to Takimoto, Maruoka and Vovk, we present underlying design methods for constructing a variety of on-line prediction algorithms based on the SWP. In particular, we shown how the typical expert model where the experts are considered to be arranged on one layer can be generalized to the case where they are laid on a tree structure so that the expert model can be applied to search for the best pruning in a straightforward fashion through dynamic programming scheme.
Cite
Text
Maruoka and Takimoto. "Structured Weight-Based Prediction Algorithms." International Conference on Algorithmic Learning Theory, 1998. doi:10.1007/3-540-49730-7_10Markdown
[Maruoka and Takimoto. "Structured Weight-Based Prediction Algorithms." International Conference on Algorithmic Learning Theory, 1998.](https://mlanthology.org/alt/1998/maruoka1998alt-structured/) doi:10.1007/3-540-49730-7_10BibTeX
@inproceedings{maruoka1998alt-structured,
title = {{Structured Weight-Based Prediction Algorithms}},
author = {Maruoka, Akira and Takimoto, Eiji},
booktitle = {International Conference on Algorithmic Learning Theory},
year = {1998},
pages = {127-142},
doi = {10.1007/3-540-49730-7_10},
url = {https://mlanthology.org/alt/1998/maruoka1998alt-structured/}
}