我们提出的自学习聚类算法[3]属于基于特征的无监督迁移学习方面的工作。这里我们考虑的问题是：现实中可能有标记的辅助数据都难以得到，在这种情况下如何 利用大量无标记数据辅助数据进行迁移学习的问题。自学习聚类的基本思想是通过同时对源数据与辅助数据进行聚类得到一个共同的特征表示，而这个新的特征表示由于基于大量的辅助数据，所以会优于仅基于源数据而产生的特 征表示，从而对聚类产生帮助。
上面提出的两种学习策略（基于特征的有监督迁移学习与无监督迁移学习）解决的都是源数据与辅助数据在同一特征空间内的基于特征的迁移学习问题。当源数据与辅助数据所在的特征空间中不同时，我们还研究了跨特征空间的基于特征的迁移学习，它也属于基于特征的迁移学习的一种。
3.异构空间下的迁移学习：翻译学习
我们提出的翻译学习[1][5]致力于解决源数据与测试数据分别属于两个不同的特征空间下的情况。在[1]中，我们使用大量容易得到的标注过文本数据去帮助 仅有少量标注的图像分类的问题，如上图所示。我们的方法基于使用那些用有两个视角的数据来构建沟通两个特征空间的桥梁。虽然这些多视角数据可能不一定能够 用来做分类用的训练数据，但是，它们可以用来构建翻译器。通过这个翻译器，我们把近邻算法和特征翻译结合在一起，将辅助数据翻译到源数据特征空间里去，用 一个统一的语言模型进行学习与分类。
引文：
[1]. Wenyuan Dai, Yuqiang Chen, Gui-Rong Xue, Qiang Yang, and Yong Yu. Translated Learning: Transfer Learning across Different Feature Spaces. Advances in Neural Information Processing Systems 21 (NIPS 2008), Vancouver, British Columbia, Canada, December 8-13, 2008.
[2]. Xiao Ling, Wenyuan Dai, Gui-Rong Xue, Qiang Yang, and Yong Yu. Spectral Domain-Transfer Learning. In Proceedings of the Fourteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2008), Pages 488-496, Las Vegas, Nevada, USA, August 24-27, 2008.
[3]. Wenyuan Dai, Qiang Yang, Gui-Rong Xue and Yong Yu. Self-taught Clustering. In Proceedings of the Twenty-Fifth International Conference on Machine Learning (ICML 2008), pages 200-207, Helsinki, Finland, 5-9 July, 2008.
[4]. Gui-Rong Xue, Wenyuan Dai, Qiang Yang and Yong Yu. Topic-bridged PLSA for Cross-Domain Text Classification. In Proceedings of the Thirty-first International ACM SIGIR Conference on Research and Development on Information Retrieval (SIGIR2008), pages 627-634, Singapore, July 20-24, 2008.
[5]. Xiao Ling, Gui-Rong Xue, Wenyuan Dai, Yun Jiang, Qiang Yang and Yong Yu. Can Chinese Web Pages be Classified with English Data Source? In Proceedings the Seventeenth International World Wide Web Conference (WWW2008), Pages 969-978, Beijing, China, April 21-25, 2008.
[6]. Xiao Ling, Wenyuan Dai, Gui-Rong Xue and Yong Yu. Knowledge Transferring via Implicit Link Analysis. In Proceedings of the Thirteenth International Conference on Database Systems for Advanced Applications (DASFAA 2008), Pages 520-528, New Delhi, India, March 19-22, 2008.
[7]. Wenyuan Dai, Gui-Rong Xue, Qiang Yang and Yong Yu. Co-clustering based Classification for Out-of-domain Documents. In Proceedings of the Thirteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2007), Pages 210-219, San Jose, California, USA, Aug 12-15, 2007.
[8]. Wenyuan Dai, Gui-Rong Xue, Qiang Yang and Yong Yu. Transferring Naive Bayes Classifiers for Text Classification. In Proceedings of the Twenty-Second National Conference on Artificial Intelligence (AAAI 2007), Pages 540-545, Vancouver, British Columbia, Canada, July 22-26, 2007.
[9]. Wenyuan Dai, Qiang Yang, Gui-Rong Xue and Yong Yu. Boosting for Transfer Learning. In Proceedings of the Twenty-Fourth International Conference on Machine Learning (ICML 2007), Pages 193-200, Corvallis, Oregon, USA, June 20-24, 2007.
[10]. Dikan Xing, Wenyuan Dai, Gui-Rong Xue and Yong Yu. Bridged Refinement for Transfer Learning. In Proceedings of the Eleventh European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD 2007), Pages 324-335, Warsaw, Poland, September 17-21, 2007. （Best Student Paper Award）
[11]. Xin Zhang, Wenyuan Dai, Gui-Rong Xue and Yong Yu. Adaptive Email Spam Filtering based on Information Theory. In Proceedings of the Eighth International Conference on Web Information Systems Engineering (WISE 2007), Pages 159–170, Nancy, France, December 3-7, 2007.