Learning for amalgamation: A multi-source transfer learning framework for sentiment classification

• Main Authors: Nguyen, Cuong V., Le, Khiem H., PHAM, Hong Quang, Pham, Quang H., Nguyen, Binh T.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2022
• Subjects: LIFA; Low-resource NLP; Mixture of experts; Sentiment classification; Transfer learning; Databases and Information Systems; East Asian Languages and Societies
• Online Access: https://ink.library.smu.edu.sg/sis_research/6948; https://ink.library.smu.edu.sg/context/sis_research/article/7951/viewcontent/LearningAmalgation_av.pdf
• Institution: Singapore Management University

Transfer learning plays an essential role in Deep Learning, which can remarkably improve the performance of the target domain, whose training data is not sufficient. Our work explores beyond the common practice of transfer learning with a single pre-trained model. We focus on the task of Vietnamese...