@inproceedings{morency-etal-2022-tutorial,
title = "Tutorial on Multimodal Machine Learning",
author = "Morency, Louis-Philippe and
Liang, Paul Pu and
Zadeh, Amir",
editor = "Ballesteros, Miguel and
Tsvetkov, Yulia and
Alm, Cecilia O.",
booktitle = "Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Tutorial Abstracts",
month = jul,
year = "2022",
address = "Seattle, United States",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.naacl-tutorials.5",
doi = "10.18653/v1/2022.naacl-tutorials.5",
pages = "33--38",
abstract = "Multimodal machine learning involves integrating and modeling information from multiple heterogeneous sources of data. It is a challenging yet crucial area with numerous real-world applications in multimedia, affective computing, robotics, finance, HCI, and healthcare. This tutorial, building upon a new edition of a survey paper on multimodal ML as well as previously-given tutorials and academic courses, will describe an updated taxonomy on multimodal machine learning synthesizing its core technical challenges and major directions for future research.",
}
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%0 Conference Proceedings
%T Tutorial on Multimodal Machine Learning
%A Morency, Louis-Philippe
%A Liang, Paul Pu
%A Zadeh, Amir
%Y Ballesteros, Miguel
%Y Tsvetkov, Yulia
%Y Alm, Cecilia O.
%S Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Tutorial Abstracts
%D 2022
%8 July
%I Association for Computational Linguistics
%C Seattle, United States
%F morency-etal-2022-tutorial
%X Multimodal machine learning involves integrating and modeling information from multiple heterogeneous sources of data. It is a challenging yet crucial area with numerous real-world applications in multimedia, affective computing, robotics, finance, HCI, and healthcare. This tutorial, building upon a new edition of a survey paper on multimodal ML as well as previously-given tutorials and academic courses, will describe an updated taxonomy on multimodal machine learning synthesizing its core technical challenges and major directions for future research.
%R 10.18653/v1/2022.naacl-tutorials.5
%U https://aclanthology.org/2022.naacl-tutorials.5
%U https://doi.org/10.18653/v1/2022.naacl-tutorials.5
%P 33-38
Markdown (Informal)
[Tutorial on Multimodal Machine Learning](https://aclanthology.org/2022.naacl-tutorials.5) (Morency et al., NAACL 2022)
ACL
- Louis-Philippe Morency, Paul Pu Liang, and Amir Zadeh. 2022. Tutorial on Multimodal Machine Learning. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Tutorial Abstracts, pages 33–38, Seattle, United States. Association for Computational Linguistics.