Partially Supervised Classification of Text Documents
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
Facial expression recognition from video sequences: temporal and static modeling
Computer Vision and Image Understanding - Special issue on Face recognition
Building Text Classifiers Using Positive and Unlabeled Examples
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Active Appearance Models Revisited
International Journal of Computer Vision
Learning and evaluating classifiers under sample selection bias
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Online Selection of Discriminative Tracking Features
IEEE Transactions on Pattern Analysis and Machine Intelligence
Estimating the Support of a High-Dimensional Distribution
Neural Computation
Face Description with Local Binary Patterns: Application to Face Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Boosting for transfer learning
Proceedings of the 24th international conference on Machine learning
Cross-domain video concept detection using adaptive svms
Proceedings of the 15th international conference on Multimedia
Proceedings of the 25th international conference on Machine learning
Using Wikipedia for Co-clustering Based Cross-Domain Text Classification
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
Facial expression recognition based on Local Binary Patterns: A comprehensive study
Image and Vision Computing
Domain adaptation for statistical classifiers
Journal of Artificial Intelligence Research
IEEE Transactions on Pattern Analysis and Machine Intelligence
Bregman Divergence-Based Regularization for Transfer Subspace Learning
IEEE Transactions on Knowledge and Data Engineering
IEEE Transactions on Knowledge and Data Engineering
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing
What you saw is not what you get: Domain adaptation using asymmetric kernel transforms
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Localizing parts of faces using a consensus of exemplars
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Automatically Detecting Pain in Video Through Facial Action Units
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Domain adaptation for object recognition: An unsupervised approach
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
Learning person-specific models for facial expression and action unit recognition
Pattern Recognition Letters
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When training and testing data are drawn from different distributions, most statistical models need to be retrained using the newly collected data. Transfer learning is a family of algorithms that improves the classifier learning in a target domain of interest by transferring the knowledge from one or multiple source domains, where the data falls in a different distribution. In this paper, we consider a new scenario of transfer learning for two-class classification, where only data samples from one of the two classes (e.g., the negative class) are available in the target domain. We introduce a regression-based one-class transfer learning algorithm to tackle this new problem. In contrast to the traditional discriminative feature selection, which seeks the best classification performance in the training data, we propose a new framework to learn the most transferable discriminative features suitable for our transfer learning. The experiment demonstrates improved performance in the applications of facial expression recognition and facial landmark detection.