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...
Tian, Y., & Feng, Y. (2022). Transfer learning under high-dimensional generalized linear models. Journal of the American Statistical Association, (pp. 1–14). Graphical Models He, Y., Li, Q., Hu, Q., & Liu, L. (2022). Transfer learning in high‐dimensional semiparametric graphical m...
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:...
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...
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...
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
Deep learning techniques have proven to be effective in solving the facial emotion recognition (FER) problem. However, it demands a significant amount of supervision data which is often unavailable due to privacy and ethical concerns. In this paper, we p
) and decoder’s architecture, though, have to depend on the task as the output structures of different tasks vary; for all pixel-to-pixel tasks, e.g. normal estimation, the decoder is a 15-layer fully convolutional network; for low dimensional tasks, e.g. vanishing points, it consists ...
The study investigates the potential of transfer learning–based models for automatically diagnosing diseases like COVID-19 to assist the medical force, especially in times of an outbreak. In the proposed work, a deep learning model, i.e., truncated VGG16 (Visual Geometry Group from Oxford) is...