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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence

Bivariate Beta-LSTM

February 1, 2023

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Authors

Kyungwoo Song

KAIST


JoonHo Jang

KAIST


Seung jae Shin

KAIST


Il-Chul Moon

KAIST


DOI:

10.1609/aaai.v34i04.6039


Abstract:

Long Short-Term Memory (LSTM) infers the long term dependency through a cell state maintained by the input and the forget gate structures, which models a gate output as a value in [0,1] through a sigmoid function. However, due to the graduality of the sigmoid function, the sigmoid gate is not flexible in representing multi-modality or skewness. Besides, the previous models lack modeling on the correlation between the gates, which would be a new method to adopt inductive bias for a relationship between previous and current input. This paper proposes a new gate structure with the bivariate Beta distribution. The proposed gate structure enables probabilistic modeling on the gates within the LSTM cell so that the modelers can customize the cell state flow with priors and distributions. Moreover, we theoretically show the higher upper bound of the gradient compared to the sigmoid function, and we empirically observed that the bivariate Beta distribution gate structure provides higher gradient values in training. We demonstrate the effectiveness of the bivariate Beta gate structure on the sentence classification, image classification, polyphonic music modeling, and image caption generation.

Topics: AAAI

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HOW TO CITE:

Kyungwoo Song||JoonHo Jang||Seung jae Shin||Il-Chul Moon Bivariate Beta-LSTM Proceedings of the AAAI Conference on Artificial Intelligence (2020) 5818-5825.

Kyungwoo Song||JoonHo Jang||Seung jae Shin||Il-Chul Moon Bivariate Beta-LSTM AAAI 2020, 5818-5825.

Kyungwoo Song||JoonHo Jang||Seung jae Shin||Il-Chul Moon (2020). Bivariate Beta-LSTM. Proceedings of the AAAI Conference on Artificial Intelligence, 5818-5825.

Kyungwoo Song||JoonHo Jang||Seung jae Shin||Il-Chul Moon. Bivariate Beta-LSTM. Proceedings of the AAAI Conference on Artificial Intelligence 2020 p.5818-5825.

Kyungwoo Song||JoonHo Jang||Seung jae Shin||Il-Chul Moon. 2020. Bivariate Beta-LSTM. "Proceedings of the AAAI Conference on Artificial Intelligence". 5818-5825.

Kyungwoo Song||JoonHo Jang||Seung jae Shin||Il-Chul Moon. (2020) "Bivariate Beta-LSTM", Proceedings of the AAAI Conference on Artificial Intelligence, p.5818-5825

Kyungwoo Song||JoonHo Jang||Seung jae Shin||Il-Chul Moon, "Bivariate Beta-LSTM", AAAI, p.5818-5825, 2020.

Kyungwoo Song||JoonHo Jang||Seung jae Shin||Il-Chul Moon. "Bivariate Beta-LSTM". Proceedings of the AAAI Conference on Artificial Intelligence, 2020, p.5818-5825.

Kyungwoo Song||JoonHo Jang||Seung jae Shin||Il-Chul Moon. "Bivariate Beta-LSTM". Proceedings of the AAAI Conference on Artificial Intelligence, (2020): 5818-5825.

Kyungwoo Song||JoonHo Jang||Seung jae Shin||Il-Chul Moon. Bivariate Beta-LSTM. AAAI[Internet]. 2020[cited 2023]; 5818-5825.


ISSN: 2374-3468


Published by AAAI Press, Palo Alto, California USA
Copyright 2022, Association for the Advancement of
Artificial Intelligence 1900 Embarcadero Road, Suite
101, Palo Alto, California 94303 All Rights Reserved

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