Domain Generalization using Ensemble Learning

• URL: http://arxiv.org/abs/2103.10257v1
• Date: Thu, 18 Mar 2021 13:50:36 GMT
• Title: Domain Generalization using Ensemble Learning
• Authors: Yusuf Mesbah, Youssef Youssry Ibrahim, Adil Mehood Khan
• Abstract summary: We tackle the problem of a model's weak generalization when it is trained on a single source domain. From this perspective, we build an ensemble model on top of base deep learning models trained on a single source to enhance the generalization of their collective prediction.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Domain generalization is a sub-field of transfer learning that aims at bridging the gap between two different domains in the absence of any knowledge about the target domain. Our approach tackles the problem of a model's weak generalization when it is trained on a single source domain. From this perspective, we build an ensemble model on top of base deep learning models trained on a single source to enhance the generalization of their collective prediction. The results achieved thus far have demonstrated promising improvements of the ensemble over any of its base learners.

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