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[HTML][HTML] A comparison review of transfer learning and self-supervised learning: Definitions, applications, advantages and limitations
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 …
learning research. However, one persistent challenge is the scarcity of labelled training …
A survey on self-supervised learning: Algorithms, applications, and future trends
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 …
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
This comprehensive survey explored the evolving landscape of generative Artificial
Intelligence (AI), with a specific focus on the transformative impacts of Mixture of Experts …
Intelligence (AI), with a specific focus on the transformative impacts of Mixture of Experts …
Towards universal sequence representation learning for recommender systems
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 …
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
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 …
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
With the explosive growth of online information, the significant application value of
recommender systems has received considerable attention. Since user–item interactions …
recommender systems has received considerable attention. Since user–item interactions …