We study the more challenging case of unsupervised transductive transfer learning, where no la- beled data from the target domain are available at training.
We describe some current state-of-the-art inductive and transductive approaches and then adapt these models to the problem of transfer learning for protein name ...
The problem of transfer learning, where information gained in one learning task is used to improve performance in another related task, is an important new ...
In this paper we examine the problem of domain adap- tation for protein name extraction. First we define the gen- eral problem of transfer learning and the ...
This paper shows that the accuracy of learned text classifiers can be improved by augmenting a small number of labeled training documents with a large pool of ...
We describe some current state-of-the-art inductive and transductive approaches and then adapt these models to the problem of transfer learning for protein name ...
The problem of transfer learning, where information gained in one learning task is used to improve performance in another related task, is an important new ...
We describe some current state-of-the-art inductive and transductive approaches and then adapt these models to the problem of transfer learning for protein name ...
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May 15, 2024 · This review paper explores the recent applications of these pre-training methods in various fields within the past three years.
Download ppt "A Comparative Study of Methods for Transductive Transfer Learning Andrew Arnold, Ramesh Nallapati, William W. Cohen Machine Learning Department ...