Knowledge-aware Zero-Shot Learning: Survey and Perspective-Reference-Cited by-同舟云学术

Knowledge-aware Zero-Shot Learning: Survey and Perspective

Published:2021-08 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence
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Author:

Chen Jiaoyan¹,Geng Yuxia²,Chen Zhuo²,Horrocks Ian¹,Z. Pan Jeff³,Chen Huajun²

Affiliation:

1. University of Oxford

2. Zhejiang University

3. The University of Edinburgh

Abstract

Zero-shot learning (ZSL) which aims at predicting classes that have never appeared during the training using external knowledge (a.k.a. side information) has been widely investigated. In this paper we present a literature review towards ZSL in the perspective of external knowledge, where we categorize the external knowledge, review their methods and compare different external knowledge. With the literature review, we further discuss and outlook the role of symbolic knowledge in addressing ZSL and other machine learning sample shortage issues.

Publisher

International Joint Conferences on Artificial Intelligence Organization

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