Fairness-Aware Multimodal Learning in Automatic Video Interview Assessment

Author:

Kim Changwoo1ORCID,Choi Jinho2ORCID,Yoon Jongyeon3ORCID,Yoo Daehun2,Lee Woojin4ORCID

Affiliation:

1. Department of Artificial Intelligence, Dongguk University, Jung-gu, Seoul, South Korea

2. Genesis Laboratory, Jung-gu, Seoul, South Korea

3. Department of Statistics, Dongguk University, Jung-gu, Seoul, South Korea

4. College of AI Convergence, Dongguk University, Jung-gu, Seoul, South Korea

Funder

Genesis Laboratory Company

National Research Foundation of Korea

Korean Government through the Ministry of Science and Information and Communications Technology

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Reference49 articles.

1. Towards principled methods for training generative adversarial networks;arjovsky;arXiv 1701 04862,2017

2. The Wasserstein distances

3. Hire me: Computational Inference of Hirability in Employment Interviews Based on Nonverbal Behavior

4. Wasserstein generative adversarial networks;arjovsky;Proc Int Conf Mach Learn,2017

5. Optimized pre-processing for discrimination prevention;calmon;Proc Adv Neural Inf Process Syst,2017

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