ICML 2020poster2 citations
Representing Unordered Data Using Complex-Weighted Multiset Automata
Justin DeBenedetto, David Chiang
Abstract
Unordered, variable-sized inputs arise in many settings across multiple fields. The ability for set- and multiset-oriented neural networks to handle this type of input has been the focus of much work in recent years. We propose to represent multisets using complex-weighted
BibTeX
@InProceedings{pmlr-v119-debenedetto20a,
title = {Representing Unordered Data Using Complex-Weighted Multiset Automata},
author = {{DeBenedetto}, Justin and Chiang, David},
booktitle = {Proceedings of the 37th International Conference on Machine Learning},
pages = {2412--2420},
year = {2020},
editor = {III, Hal Daumé and Singh, Aarti},
volume = {119},
series = {Proceedings of Machine Learning Research},
month = {13--18 Jul},
publisher = {PMLR},
pdf = {http://proceedings.mlr.press/v119/debenedetto20a/debenedetto20a.pdf},
url = {https://proceedings.mlr.press/v119/debenedetto20a.html},
abstract = {Unordered, variable-sized inputs arise in many settings across
multiple fields. The ability for set- and multiset-oriented neural
networks to handle this type of input has been the focus of much
work in recent years. We propose to represent multisets using
complex-weighted