[HTML][HTML] A comparison review of transfer learning and self-supervised learning: Definitions, applications, advantages and limitations

Z Zhao, L Alzubaidi, J Zhang, Y Duan, Y Gu - Expert Systems with …, 2024‏ - Elsevier
Deep learning has emerged as a powerful tool in various domains, revolutionising machine
learning research. However, one persistent challenge is the scarcity of labelled training …

A survey on self-supervised learning: Algorithms, applications, and future trends

J Gui, T Chen, J Zhang, Q Cao, Z Sun… - IEEE Transactions on …, 2024‏ - ieeexplore.ieee.org
Deep supervised learning algorithms typically require a large volume of labeled data to
achieve satisfactory performance. However, the process of collecting and labeling such data …

Representation learning with large language models for recommendation

X Ren, W Wei, L ** the generative artificial intelligence (ai) research landscape
TR McIntosh, T Susnjak, T Liu, P Watters… - arxiv preprint arxiv …, 2023‏ - arxiv.org
This comprehensive survey explored the evolving landscape of generative Artificial
Intelligence (AI), with a specific focus on the transformative impacts of Mixture of Experts …

Towards universal sequence representation learning for recommender systems

Y Hou, S Mu, WX Zhao, Y Li, B Ding… - Proceedings of the 28th …, 2022‏ - dl.acm.org
In order to develop effective sequential recommenders, a series of sequence representation
learning (SRL) methods are proposed to model historical user behaviors. Most existing SRL …

Pre-train, prompt, and recommendation: A comprehensive survey of language modeling paradigm adaptations in recommender systems

P Liu, L Zhang, JA Gulla - Transactions of the Association for …, 2023‏ - direct.mit.edu
The emergence of Pre-trained Language Models (PLMs) has achieved tremendous success
in the field of Natural Language Processing (NLP) by learning universal representations on …

BLoG: Bootstrapped graph representation learning with local and global regularization for recommendation

M Li, L Zhang, L Cui, L Bai, Z Li, X Wu - Pattern Recognition, 2023‏ - Elsevier
With the explosive growth of online information, the significant application value of
recommender systems has received considerable attention. Since user–item interactions …