Survey on transfer learning research
庄福振， 罗平， 何清， 史忠植 - Journal of Software, 2014 - jos.org.cn
近年来, 迁移学习已经引起了广泛的关注和研究. 迁移学习是运用已存有的知识对不同但相关
领域问题进行求解的一种新的机器学习方法. 它放宽了传统机器学习中的两个基本假设:(1) …
领域问题进行求解的一种新的机器学习方法. 它放宽了传统机器学习中的两个基本假设:(1) …
[图书][B] Machine learning for text: An introduction
CC Aggarwal, CC Aggarwal - 2018 - Springer
The extraction of useful insights from text with various types of statistical algorithms is
referred to as text mining, text analytics, or machine learning from text. The choice of …
referred to as text mining, text analytics, or machine learning from text. The choice of …
Ddtcdr: Deep dual transfer cross domain recommendation
P Li, A Tuzhilin - Proceedings of the 13th International Conference on …, 2020 - dl.acm.org
Cross domain recommender systems have been increasingly valuable for helping
consumers identify the most satisfying items from different categories. However, previously …
consumers identify the most satisfying items from different categories. However, previously …
Transfer learning
SJ Pan - Learning, 2020 - api.taylorfrancis.com
Supervised machine learning techniques have already been widely studied and applied to
various real-world applications. However, most existing supervised algorithms work well …
various real-world applications. However, most existing supervised algorithms work well …
Transfer learning with graph co-regularization
Transfer learning is established as an effective technology to leverage rich labeled data from
some source domain to build an accurate classifier for the target domain. The basic …
some source domain to build an accurate classifier for the target domain. The basic …
Bridging text visualization and mining: A task-driven survey
Visual text analytics has recently emerged as one of the most prominent topics in both
academic research and the commercial world. To provide an overview of the relevant …
academic research and the commercial world. To provide an overview of the relevant …
Dual metric learning for effective and efficient cross-domain recommendations
P Li, A Tuzhilin - IEEE Transactions on Knowledge and Data …, 2021 - ieeexplore.ieee.org
Cross domain recommender systems have been increasingly valuable for helping
consumers identify useful items in different applications. However, existing cross-domain …
consumers identify useful items in different applications. However, existing cross-domain …
Dual attentive sequential learning for cross-domain click-through rate prediction
P Li, Z Jiang, M Que, Y Hu, A Tuzhilin - Proceedings of the 27th ACM …, 2021 - dl.acm.org
Cross domain recommender system constitutes a powerful method to tackle the cold-start
and sparsity problem by aggregating and transferring user preferences across multiple …
and sparsity problem by aggregating and transferring user preferences across multiple …
Dual attention transfer in session-based recommendation with multi-dimensional integration
Session-based recommendation (SBR) is widely used in e-commerce to predict the
anonymous user's next click action according to a short sequence. Many previous studies …
anonymous user's next click action according to a short sequence. Many previous studies …