Learning discriminative correlation subspace for heterogeneous domain adaptation

Yuguang Yan, Wen Li, Kwok Po NG, Mingkui Tan, Hanrui Wu, Huaqing Min, Qingyao Wu*

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

27 Citations (Scopus)

Abstract

Domain adaptation aims to reduce the effort on collecting and annotating target data by leveraging knowledge from a different source domain. The domain adaptation problem will become extremely challenging when the feature spaces of the source and target domains are different, which is also known as the heterogeneous domain adaptation (HDA) problem. In this paper, we propose a novel HDA method to find the optimal discriminative correlation subspace for the source and target data. The discriminative correlation subspace is inherited from the canonical correlation subspace between the source and target data, and is further optimized to maximize the discriminative ability for the target domain classifier. We formulate a joint objective in order to simultaneously learn the discriminative correlation subspace and the target domain classifier. We then apply an alternating direction method of multiplier (ADMM) algorithm to address the resulting non-convex optimization problem. Comprehensive experiments on two real-world data sets demonstrate the effectiveness of the proposed method compared to the state-of-the-art methods.

Original languageEnglish
Title of host publication26th International Joint Conference on Artificial Intelligence, IJCAI 2017
EditorsCarles Sierra
PublisherInternational Joint Conferences on Artificial Intelligence
Pages3252-3258
Number of pages7
ISBN (Electronic)9780999241103
DOIs
Publication statusPublished - 2017
Event26th International Joint Conference on Artificial Intelligence, IJCAI 2017 - Melbourne, Australia, Melbourne, Australia
Duration: 19 Aug 201725 Aug 2017

Publication series

NameIJCAI International Joint Conference on Artificial Intelligence
Volume0
ISSN (Print)1045-0823

Conference

Conference26th International Joint Conference on Artificial Intelligence, IJCAI 2017
Country/TerritoryAustralia
CityMelbourne
Period19/08/1725/08/17

Scopus Subject Areas

  • Artificial Intelligence

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