Transfer learningIn this work, we study the transfer learning problem under high-dimensional generalized linear models (GLMs), which aim to improve the fit on target data by borrowing information from useful source data. Given which sources to transfer, we propose a transfer learning algorithm on ...
Transfer learning under high-dimensional generalized linear models. Tian, Y., & Feng, Y. (2022). Journal of the American Statistical Association, (pp. 1–14). Transfer Learning for Functional Linear Regression with Structural Interpretability. Haotian Lin and Matthew Reimherr Residual Importance Weig...
Li, S., Zhang, L., Cai, T. T., & Li, H. (2023). Estimation and inference for high-dimensional generalized linear models with knowledge transfer. Journal of the American Statistical Association, (pp. 1–12). Tian, Y., & Feng, Y. (2022). Transfer learning under high-dimensional gen...
Transfer learning for high-dimensional linear regression via the elastic net In this paper, the high-dimensional linear regression problem is explored via the Elastic Net under the transfer learning framework. Within this framework,... K Meng,Y Gai,X Wang,... - Knowledge-Based Systems 被引量:...
It is common to perform transfer learning with natural language processing problems that use text as input or output. For these types of problems, a word embedding is used that is a mapping of words to a high-dimensional continuous vector space where different words with a similar meaning have...
Transfer Learning with Language Data It is common to perform transfer learning with natural language processing problems that use text as input or output. For these types of problems, a word embedding is used that is a mapping of words to a high-dimensional continuous vector space where different...
转http://www.zhizhihu.com/html/y2009/790.html迁移学习(Transfer Learning)TL在机器学习领域,迁移学习(Transfer learning)是一个比较新的名词。目前国内做这个方面的很少,我目前只知道香港科技大学杨强教授及上海交大的机器学习
Accelerating the design of Ni-based single crystal (SX) superalloys with superior creep resistance at ultrahigh temperatures is a desirable goal but extremely challenging task. In the present work, a deep transfer learning neural network with physical co
where the features generated by the pre-trained networks are represented as maximal correlation functions. We particularly look into the multivariate correlation23of the source features with the target domain, thereby capturing the complex association between the high-dimensional source features and the ta...
Transfer learning (TL) appears to be a potential method for transferring information from general to specialized activities. Unfortunately, experimenting u