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Title: GitHub - fancycheung/transferlearning: Resources and codes about transfer learning and domain adaptation--迁移学习 · GitHub

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Description: Resources and codes about transfer learning and domain adaptation--迁移学习 - fancycheung/transferlearning

Open Graph Description: Resources and codes about transfer learning and domain adaptation--迁移学习 - fancycheung/transferlearning

X Description: Resources and codes about transfer learning and domain adaptation--迁移学习 - fancycheung/transferlearning

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https://github.com/fancycheung/transferlearning#关于迁移学习的一些资料
行为识别https://github.com/jindongwang/activityrecognition
机器学习https://github.com/jindongwang/MachineLearning
https://github.com/fancycheung/transferlearning#目录-table-of-contents
最新 Latesthttps://github.com/fancycheung/transferlearning#0latest
迁移学习简介 Introduction to transfer learninghttps://github.com/fancycheung/transferlearning#1%E8%BF%81%E7%A7%BB%E5%AD%A6%E4%B9%A0%E7%AE%80%E4%BB%8B
迁移学习的综述文章 Survey papers for transfer learninghttps://github.com/fancycheung/transferlearning#2%E8%BF%81%E7%A7%BB%E5%AD%A6%E4%B9%A0%E7%9A%84%E7%BB%BC%E8%BF%B0%E6%96%87%E7%AB%A0
Matlab和Python代码 Available codeshttps://github.com/jindongwang/transferlearning/tree/master/code
迁移学习代表性研究学者 Scholarshttps://github.com/fancycheung/transferlearning#4%E8%BF%81%E7%A7%BB%E5%AD%A6%E4%B9%A0%E4%BB%A3%E8%A1%A8%E6%80%A7%E7%A0%94%E7%A9%B6%E5%AD%A6%E8%80%85
迁移学习相关的硕博士论文 Thesishttps://github.com/fancycheung/transferlearning#5%E8%BF%81%E7%A7%BB%E5%AD%A6%E4%B9%A0%E7%9B%B8%E5%85%B3%E7%9A%84%E7%A1%95%E5%8D%9A%E5%A3%AB%E8%AE%BA%E6%96%87
Domain adaptation相关的文章 Domain adaptation articleshttps://github.com/jindongwang/transferlearning/blob/master/doc/domain_adaptation.md
代表方法及文章解读 Popular methods and my explanationshttps://github.com/fancycheung/transferlearning#%E4%BB%A3%E8%A1%A8%E6%80%A7%E7%9A%84%E6%96%B9%E6%B3%95%E5%8F%8A%E6%96%87%E7%AB%A0
迁移学习用于行为识别的文章总结 Transfer learningfor activity recognitionhttps://github.com/jindongwang/activityrecognition/blob/master/notes/%E8%BF%81%E7%A7%BB%E5%AD%A6%E4%B9%A0%E7%94%A8%E4%BA%8E%E8%A1%8C%E4%B8%BA%E8%AF%86%E5%88%AB.md
常用数据集 Datasetshttps://github.com/jindongwang/transferlearning/blob/master/doc/dataset.md
Contributinghttps://github.com/fancycheung/transferlearning#contributing
https://github.com/fancycheung/transferlearning#0latest
Learning To Transferhttps://arxiv.org/abs/1708.05629
我的解读https://zhuanlan.zhihu.com/p/28888554
Deep Transfer Learning with Joint Adaptation Networkshttps://2017.icml.cc/Conferences/2017/Schedule?showEvent=1117
代码https://github.com/thuml/transfer-caffe
https://github.com/fancycheung/transferlearning#1迁移学习简介
文档https://github.com/jindongwang/transferlearning/blob/master/doc/%E8%BF%81%E7%A7%BB%E5%AD%A6%E4%B9%A0%E7%AE%80%E4%BB%8B.md
PPT(英文)http://jd92.wang/assets/files/l03_transferlearning.pdf
PPT(中文)http://jd92.wang/assets/files/l08_tl_zh.pdf
https://www.youtube.com/watch?v=qD6iD4TFsdQhttps://www.youtube.com/watch?v=qD6iD4TFsdQ
https://github.com/fancycheung/transferlearning#2迁移学习的综述文章
一些迁移学习的综述文章https://mega.nz/#F!sb4ChYoa!37LU6HGJ6LhQC1OYYBglIw
A survey on transfer learninghttps://mega.nz/#!hapCXZjQ!p9PpMK0VYWy6Li7QBZ3eVDgaHYUc1MewRFMcjfXAA7s
Cross-dataset recognition: a surveyhttps://arxiv.org/abs/1705.04396
A survey on multi-task learninghttps://arxiv.org/abs/1707.08114
A survey of transfer learninghttps://mega.nz/#!RfwwiBYS!7mM4juZY-oslxNtG_mv1XhV4zJknzpDM4QkD14S91_s
迁移学习应用于行为识别https://mega.nz/#!RfwwiBYS!7mM4juZY-oslxNtG_mv1XhV4zJknzpDM4QkD14S91_s
迁移学习与增强学习https://mega.nz/#!RDpiRDCL!LSMgyjV69YEiFE2D0quKkrr_t7bEOYtsnx8BkTxniKo
多个源域进行迁移的综述https://mega.nz/#!UPRTBIAS!HcjUwI_yGe3IrWCFfBxHF9nd8CFt0GTzjIyMMxdUuv0
视觉domain adaptation综述https://mega.nz/#!hWQ3HLhJ!GTCIUTVDcmnn3f7-Ulhjs_MxGv6xnFyp1nayemt9Nis
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https://github.com/fancycheung/transferlearning#3代码
这里https://github.com/jindongwang/transferlearning/tree/master/code
https://github.com/fancycheung/transferlearning#4迁移学习代表性研究学者
Qiang Yanghttp://www.cs.ust.hk/~qyang/
Google scholarhttps://scholar.google.com/citations?user=1LxWZLQAAAAJ&hl=zh-CN
Sinno Jialin Panhttp://www.ntu.edu.sg/home/sinnopan/
Google scholarhttps://scholar.google.com/citations?user=P6WcnfkAAAAJ&hl=zh-CN
Wenyuan Daihttps://scholar.google.com.sg/citations?user=AGR9pP0AAAAJ&hl=zh-CN
Lixin Duanhttp://www.lxduan.info/
Fuzhen Zhuanghttp://www.intsci.ac.cn/users/zhuangfuzhen/
Google scholarhttps://scholar.google.com/citations?user=klJBYrAAAAAJ&hl=zh-CN&oi=ao
Mingsheng Longhttp://ise.thss.tsinghua.edu.cn/~mlong/
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https://github.com/fancycheung/transferlearning#5迁移学习相关的硕博士论文
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Boqing Gonghttps://pdfs.semanticscholar.org/71b0/38958df0b7855fc7b8b8e7dcde8537a7c1ad.pdf
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戴文渊https://mega.nz/#!UehghTCK!9KPD4FwWpHoZmYCmweF0y67Sft7KzTi8F_ZIUA15-QE
赵中堂https://mega.nz/#!cKowSJSD!NLPQ01oSBYXughH9F1toFqdFoYY7JsPQMZlIYtn2-LA
完整版https://mega.nz/#F!YHIFxJAL!Ts413E2dbEc_2az4dhb_Jg
https://github.com/fancycheung/transferlearning#6domain-adaptation相关的文章
Domain adaptationhttps://github.com/jindongwang/transferlearning/blob/master/doc/domain_adaptation.md
https://github.com/fancycheung/transferlearning#代表性的方法及文章
Domain adaptation via tranfer component analysishttps://mega.nz/#!JTwElLrL!j5-TanhHCMESsGBNvY6I_hX6uspsrTxyopw8bPQ2azU
我的解读https://zhuanlan.zhihu.com/p/26764147?group_id=844611188275965952
Transfer Feature Learning with Joint Distribution Adaptationhttp://ise.thss.tsinghua.edu.cn/~mlong/doc/joint-distribution-adaptation-iccv13.pdf
我的解读https://zhuanlan.zhihu.com/p/27336930
Geodesic flow kernel for unsupervised domain adaptationhttps://mega.nz/#!tDY1lCSD!flMSgl-0uIswpSFL3sdZgKi6fOyFVLtcO8P6SE0OUPU
我的解读https://zhuanlan.zhihu.com/p/27782708
Domain invariant transfer kernel learninghttps://mega.nz/#!tOoCCRhB!YyoorOUcp6XIPPd6A0s7qglYnaSiRJFEQBphtZ2c58Q
我的解读https://zhuanlan.zhihu.com/p/27657910
深度联合适配网络http://proceedings.mlr.press/v70/long17a.html
记与迁移学习大牛杨强教授的第二次会面https://zhuanlan.zhihu.com/p/26260083
https://github.com/fancycheung/transferlearning#记与迁移学习大牛杨强教授的第二次会面
迁移学习用于行为识别的文章总结https://github.com/jindongwang/activityrecognition/blob/master/notes/%E8%BF%81%E7%A7%BB%E5%AD%A6%E4%B9%A0%E7%94%A8%E4%BA%8E%E8%A1%8C%E4%B8%BA%E8%AF%86%E5%88%AB.md
https://github.com/fancycheung/transferlearning#迁移学习用于行为识别的文章总结
https://github.com/fancycheung/transferlearning#未来计划
https://github.com/fancycheung/transferlearning#contributing
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