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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence / EAAI-20

Mixture of Expert/Imitator Networks: Scalable Semi-Supervised Learning Framework

February 1, 2023

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Authors

Shun Kiyono

Tohoku University


Jun Suzuki

Tohoku University


Kentaro Inui

Tohoku University


DOI:

10.1609/aaai.v33i01.33014073


Abstract:

The current success of deep neural networks (DNNs) in an increasingly broad range of tasks involving artificial intelligence strongly depends on the quality and quantity of labeled training data. In general, the scarcity of labeled data, which is often observed in many natural language processing tasks, is one of the most important issues to be addressed. Semisupervised learning (SSL) is a promising approach to overcoming this issue by incorporating a large amount of unlabeled data. In this paper, we propose a novel scalable method of SSL for text classification tasks. The unique property of our method, Mixture of Expert/Imitator Networks, is that imitator networks learn to “imitate” the estimated label distribution of the expert network over the unlabeled data, which potentially contributes a set of features for the classification. Our experiments demonstrate that the proposed method consistently improves the performance of several types of baseline DNNs. We also demonstrate that our method has the more data, better performance property with promising scalability to the amount of unlabeled data.

Topics: AAAI

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HOW TO CITE:

Shun Kiyono||Jun Suzuki||Kentaro Inui Mixture of Expert/Imitator Networks: Scalable Semi-Supervised Learning Framework Proceedings of the AAAI Conference on Artificial Intelligence (2019) 4073-4081.

Shun Kiyono||Jun Suzuki||Kentaro Inui Mixture of Expert/Imitator Networks: Scalable Semi-Supervised Learning Framework AAAI 2019, 4073-4081.

Shun Kiyono||Jun Suzuki||Kentaro Inui (2019). Mixture of Expert/Imitator Networks: Scalable Semi-Supervised Learning Framework. Proceedings of the AAAI Conference on Artificial Intelligence, 4073-4081.

Shun Kiyono||Jun Suzuki||Kentaro Inui. Mixture of Expert/Imitator Networks: Scalable Semi-Supervised Learning Framework. Proceedings of the AAAI Conference on Artificial Intelligence 2019 p.4073-4081.

Shun Kiyono||Jun Suzuki||Kentaro Inui. 2019. Mixture of Expert/Imitator Networks: Scalable Semi-Supervised Learning Framework. "Proceedings of the AAAI Conference on Artificial Intelligence". 4073-4081.

Shun Kiyono||Jun Suzuki||Kentaro Inui. (2019) "Mixture of Expert/Imitator Networks: Scalable Semi-Supervised Learning Framework", Proceedings of the AAAI Conference on Artificial Intelligence, p.4073-4081

Shun Kiyono||Jun Suzuki||Kentaro Inui, "Mixture of Expert/Imitator Networks: Scalable Semi-Supervised Learning Framework", AAAI, p.4073-4081, 2019.

Shun Kiyono||Jun Suzuki||Kentaro Inui. "Mixture of Expert/Imitator Networks: Scalable Semi-Supervised Learning Framework". Proceedings of the AAAI Conference on Artificial Intelligence, 2019, p.4073-4081.

Shun Kiyono||Jun Suzuki||Kentaro Inui. "Mixture of Expert/Imitator Networks: Scalable Semi-Supervised Learning Framework". Proceedings of the AAAI Conference on Artificial Intelligence, (2019): 4073-4081.

Shun Kiyono||Jun Suzuki||Kentaro Inui. Mixture of Expert/Imitator Networks: Scalable Semi-Supervised Learning Framework. AAAI[Internet]. 2019[cited 2023]; 4073-4081.


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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