Intra-document structural frequency features for semi-supervised domain adaptation
Proceedings of the 17th ACM conference on Information and knowledge management
Cascaded model adaptation for dialog act segmentation and tagging
Computer Speech and Language
Heterogeneous transfer learning for image clustering via the social web
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 1 - Volume 1
Transfer Learning beyond Text Classification
ACML '09 Proceedings of the 1st Asian Conference on Machine Learning: Advances in Machine Learning
Three challenges in data mining
Frontiers of Computer Science in China
Human attributes from 3D pose tracking
ECCV'10 Proceedings of the 11th European conference on computer vision conference on Computer vision: Part III
A transfer approach to detecting disease reporting events in blog social media
Proceedings of the 22nd ACM conference on Hypertext and hypermedia
DAGM'11 Proceedings of the 33rd international conference on Pattern recognition
Transfer learning for cross-company software defect prediction
Information and Software Technology
Feature subsumption for sentiment classification in multiple languages
PAKDD'10 Proceedings of the 14th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part II
Human attributes from 3D pose tracking
Computer Vision and Image Understanding
A case study on meta-generalising: a Gaussian processes approach
The Journal of Machine Learning Research
Kinship verification through transfer learning
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
Hierarchical training of multiple SVMs for personalized web filtering
PRICAI'12 Proceedings of the 12th Pacific Rim international conference on Trends in Artificial Intelligence
Inferring the demographics of search users: social data meets search queries
Proceedings of the 22nd international conference on World Wide Web
Learning person-specific models for facial expression and action unit recognition
Pattern Recognition Letters
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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 area of re- search. While previous work has studied the supervised ver- sion of this problem, 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 extrac- tion. In the process, we introduce a novel maximum entropy based technique, Iterative Feature Transformation (IFT), and show that it achieves comparable performance with state-of-the-art transductive SVMs. We also show how sim- ple relaxations, such as providing additional information like the proportion of positive examples in the test data, can significantly improve the performance of some of the trans- ductive transfer learners.