Everything about Transfer Learning (Probably the most complete repository?). Your contribution is highly valued! If you find this repo helpful, please cite it as follows:
关于迁移学习的所有资料,包括:介绍、综述文章、最新文章、代表工作及其代码、常用数据集、硕博士论文、比赛等等。(可能是目前最全的迁移学习资料库?) 欢迎一起贡献! 如果认为本仓库有用,请在你的论文和其他出版物中进行引用!
@Misc{transferlearning.xyz,
howpublished = {\url{http://transferlearning.xyz}},
title = {Everything about Transfer Learning and Domain Adapation},
author = {Wang, Jindong and others}
}
A good website to see the latest arXiv preprints by search: Transfer learning, Domain adaptation
一个很好的网站,可以直接看到最新的arXiv文章: Transfer learning, Domain adaptation
迁移学习文章汇总 Awesome transfer learning papers
Want to quickly learn transfer learning?想尽快入门迁移学习?看下面的教程。
The first transfer learning tutorial 入门教程
Video tutorials 视频教程
Brief introduction and slides 简介与ppt资料
Talk is cheap, show me the code 动手教程、代码、数据
Transfer Learning Scholars and Labs - 迁移学习领域的著名学者、代表工作及实验室介绍
Related articles by research areas:
Paperweekly: 一个推荐、分享论文的网站比较好,上面会持续整理相关的文章并分享阅读笔记。
Here are some articles on transfer learning theory and survey.
Survey (综述文章):
The most influential survey on transfer learning (最权威和经典的综述): A survey on transfer learning.
Latest survey - 较新的综述:
Survey on applications - 应用导向的综述:
Theory (理论文章):
Early transfer learning theory papers - 早期迁移学习的理论分析文章:
Latest theory papers - 近期值得注意的理论分析文章:
理论研究方面,重点关注Alex Smola、Ben-David、Bernhard Schölkopf、Arthur Gretton等人的研究。
MMD (Maximum mean discrepancy):
请见这里 | Please see HERE for some popular transfer learning codes.
Here are some transfer learning scholars and labs.
全部列表以及代表工作性见这里
Please note that this list is far not complete. A full list can be seen in here. Transfer learning is an active field. If you are aware of some scholars, please add them here.
General transfer learning algorithms and applications:
Qiang Yang:中文名杨强。香港科技大学计算机系讲座教授,迁移学习领域世界性专家。IEEE/ACM/AAAI/IAPR/AAAS fellow。[Google scholar]
Sinno Jialin Pan:杨强的学生,香港科技大学博士,现任新加坡南洋理工大学助理教授。迁移学习领域代表性综述A survey on transfer learning的第一作者(Qiang Yang是二作)。[Google scholar]
Transfer learning algorithms:
Wenyuan Dai:中文名戴文渊,上海交通大学硕士,现任第四范式人工智能创业公司CEO。迁移学习领域著名的牛人,在顶级会议上发表多篇高水平文章,每篇论文引用量巨大。[Google scholar]
Mingsheng Long:中文名龙明盛,清华大学博士,现任清华大学助理教授、博士生导师。[Google scholar]
Lixin Duan:中文名段立新,新加坡南洋理工大学博士,现就职于电子科技大学,教授。[Google scholar]
Transfer learning + computer vision
Boqing Gong:南加州大学博士,现就职于腾讯AI Lab(西雅图)。曾任中佛罗里达大学助理教授。[Google scholar]
Tatiana Tommasi:Researcher at the Italian Institute of Technology.
Vinod K Kurmi[home page]: Researcher at the Indian Institute of Technology Kanpur(India)
Transfer learning + recommendation systems
Weike Pan:中文名潘微科,杨强的学生,现任深圳大学副教授,香港科技大学博士毕业。主要做迁移学习在推荐系统方面的一些工作。 [Google Scholar]
Fuzhen Zhuang:中文名庄福振,中科院计算所博士,现任中科院计算所副研究员。[Google scholar]
Online transfer learning:
Theory:
Here are some popular thesis on transfer learning.
硕博士论文可以让我们很快地对迁移学习的相关领域做一些了解,同时,也能很快地了解概括相关研究者的工作。其中,比较有名的有
2016 Baochen Sun的Correlation Alignment for Domain Adaptation
2015 南加州大学的Boqing Gong的Kernel Methods for Unsupervised Domain Adaptation
2014 清华大学龙明盛的迁移学习问题与方法研究
2014 中科院计算所赵中堂的自适应行为识别中的迁移学习方法研究
2012 杨强的学生Hao Hu的Learning based Activity Recognition
2012 杨强的学生Wencheng Zheng的Learning with Limited Data in Sensor-based Human Behavior Prediction
2010 杨强的学生Sinno Jialin Pan的Feature-based Transfer Learning and Its Applications
2009 上海交通大学戴文渊的基于实例和特征的迁移学习算法研究
其他的文章,请见完整版。
Please see HERE for the popular transfer learning datasets and benchmark results.
这里整理了常用的公开数据集和一些已发表的文章在这些数据集上的实验结果。
See HERE for transfer learning applications.
迁移学习应用请见这里。
Call for papers:
Related projects:
If you are interested in contributing, please refer to HERE for instructions in contribution.
[Notes]This Github repo can be used by following the corresponding licenses. I want to emphasis that it may contain some PDFs or thesis, which were downloaded by me and can only be used for academic purposes. The copyrights of these materials are owned by corresponding publishers or organizations. All this are for better adademic research. If any of the authors or publishers have concerns, please contact me to delete or replace them.
[文章版权声明]这个仓库可以遵守相关的开源协议进行使用。这个仓库中包含有很多研究者的论文、硕博士论文等,都来源于在网上的下载,仅作为学术研究使用。我对其中一些文章都写了自己的浅见,希望能很好地帮助理解。这些文章的版权属于相应的出版社。如果作者或出版社有异议,请联系我进行删除。一切都是为了更好地学术!