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Title: GitHub - wayne980/transferlearning: Everything about Transfer Learning and Domain Adaptation--迁移学习 · GitHub

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https://github.com/wayne980/transferlearning#迁移学习-transfer-learning
https://opensource.org/licenses/MIT
https://github.com/wayne980/transferlearning#目录-table-of-contents
最新文章 Latesthttps://github.com/wayne980/transferlearning#0latest
迁移学习简介 Introduction to transfer learninghttps://github.com/wayne980/transferlearning#1Introduction-and-Tutorials
研究领域与相关文章 Research articles by areahttps://github.com/wayne980/transferlearning#2Transfer-Learning-Areas-and-Papers
理论与综述文章 Theoretical and survey papershttps://github.com/wayne980/transferlearning#3Theory-and-Survey
相关代码 Available codeshttps://github.com/wayne980/transferlearning#4Code
代表性研究学者 Scholarshttps://github.com/wayne980/transferlearning#5Transfer-Learning-Scholars
相关硕博士论文 Thesishttps://github.com/wayne980/transferlearning#6Transfer-Learning-Thesis
数据集及算法结果 Datasets and benchmarkhttps://github.com/wayne980/transferlearning#7Datasets-and-Benchmarks
比赛 Challenges and competitionshttps://github.com/wayne980/transferlearning#8Transfer-Learning-Challenges
迁移学习应用 Transfer learning applicationshttps://github.com/wayne980/transferlearning#Applications
其他 Other resourceshttps://github.com/wayne980/transferlearning#Other-Resources
Contributinghttps://github.com/wayne980/transferlearning#contributing
行为识别https://github.com/jindongwang/activityrecognition
机器学习https://github.com/jindongwang/MachineLearning
https://github.com/wayne980/transferlearning#0latest
迁移学习文章汇总 Awesome transfer learning papershttps://github.com/jindongwang/transferlearning/tree/master/doc/awesome_paper.md
Towards Continuous Domain adaptation for Healthcarehttps://arxiv.org/abs/1812.01281
A Hybrid Instance-based Transfer Learning Methodhttps://arxiv.org/abs/1812.01063
Exploiting Coarse-to-Fine Task Transfer for Aspect-level Sentiment Classificationhttps://arxiv.org/abs/1811.10999
Multi-Task Generative Adversarial Network for Handling Imbalanced Clinical Datahttps://arxiv.org/abs/1811.10419
CNN based dense underwater 3D scene reconstruction by transfer learning using bubble databasehttps://arxiv.org/abs/1811.09675
Moment Matching for Multi-Source Domain Adaptationhttps://arxiv.org/abs/1812.01754
Feature Matters: A Stage-by-Stage Approach for Knowledge Transferhttps://arxiv.org/abs/1812.01819
Transferring Knowledge across Learning Processeshttps://arxiv.org/abs/1812.01054
Unsupervised Domain Adaptation using Generative Models and Self-ensemblinghttps://arxiv.org/abs/1812.00479
VADRA: Visual Adversarial Domain Randomization and Augmentationhttps://arxiv.org/abs/1812.00491
更多 More...https://github.com/jindongwang/transferlearning/tree/master/doc/awesome_paper.md
https://github.com/wayne980/transferlearning#1introduction-and-tutorials
简单的中文简介 Chinese introductionhttps://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(English)http://jd92.wang/assets/files/l03_transferlearning.pdf
PPT(中文)http://jd92.wang/assets/files/l08_tl_zh.pdf
PDFhttp://jd92.wang/assets/files/l12_da.pdf
Videohttp://mp.weixin.qq.com/s?__biz=MzI5MDUyMDIxNA==&mid=2247484940&idx=2&sn=35e64e07fde9a96afbb65dbf40a945eb&chksm=ec1febf5db6862e38d5e02ff3278c61b376932a46c5628c7d9cb1769c572bfd31819c13dd468&mpshare=1&scene=1&srcid=1219JpTNZFiNDCHsTUrUxwqy#rd
PPT(Samsung)http://ise.thss.tsinghua.edu.cn/~mlong/doc/transfer-learning-talk.pdf
PPT(Google China)http://ise.thss.tsinghua.edu.cn/~mlong/doc/deep-transfer-learning-talk.pdf
《迁移学习简明手册》Transfer Learning Tutorialhttps://zhuanlan.zhihu.com/p/35352154
开发维护地址https://github.com/jindongwang/transferlearning-tutorial
台湾大学李宏毅的视频讲解(中文视频)https://www.youtube.com/watch?v=qD6iD4TFsdQ
迁移学习中的领域自适应方法(中文)http://mp.weixin.qq.com/s?__biz=MzI5MDUyMDIxNA==&mid=2247484940&idx=2&sn=35e64e07fde9a96afbb65dbf40a945eb&chksm=ec1febf5db6862e38d5e02ff3278c61b376932a46c5628c7d9cb1769c572bfd31819c13dd468&mpshare=1&scene=1&srcid=1219JpTNZFiNDCHsTUrUxwqy#rd
迁移学习领域的著名学者、代表工作及实验室介绍 Transfer Learning Scholars and Labshttps://github.com/jindongwang/transferlearning/blob/master/doc/scholar_TL.md
负迁移(negative transfer)https://www.zhihu.com/question/66492194/answer/242870418
基于深度学习和迁移学习的识花实践 Using Transfer Learning for Flower Recognitionhttps://cosx.org/2017/10/transfer-learning/
基于Pytorch的图像分类 Using Transfer Learning for Image Classificationhttps://github.com/miguelgfierro/sciblog_support/blob/master/A_Gentle_Introduction_to_Transfer_Learning/Intro_Transfer_Learning.ipynb
使用Pytorch进行finetune Using Pytorch for Fine-tunehttps://github.com/Spandan-Madan/Pytorch_fine_tuning_Tutorial
基于AlexNet和ResNet的finetune Fine-tune based on Alexnet and Resnethttps://github.com/jindongwang/transferlearning/tree/master/code/AlexNet_ResNet
更多 More...https://github.com/jindongwang/transferlearning/tree/master/code
https://github.com/wayne980/transferlearning#2transfer-learning-areas-and-papers
领域自适应(非深度) Domain Adaptation (Shallow)https://github.com/jindongwang/transferlearning/blob/master/doc/awesome_paper.md#%E9%A2%86%E5%9F%9F%E8%87%AA%E9%80%82%E5%BA%94
Domain adaptationhttps://github.com/jindongwang/transferlearning/blob/master/doc/domain_adaptation.md
在线迁移学习 Online transfer learninghttps://github.com/jindongwang/transferlearning/blob/master/doc/awesome_paper.md#%E5%9C%A8%E7%BA%BF%E8%BF%81%E7%A7%BB%E5%AD%A6%E4%B9%A0
终身迁移学习 Lifelong transfer learninghttps://github.com/jindongwang/transferlearning/blob/master/doc/awesome_paper.md#%E7%BB%88%E8%BA%AB%E8%BF%81%E7%A7%BB%E5%AD%A6%E4%B9%A0
异构迁移学习 Heterogeneous Transfer Learninghttps://github.com/jindongwang/transferlearning/blob/master/doc/awesome_paper.md#%E5%BC%82%E6%9E%84%E8%BF%81%E7%A7%BB%E5%AD%A6%E4%B9%A0
深度迁移学习 Deep Transfer Learninghttps://github.com/jindongwang/transferlearning/blob/master/doc/awesome_paper.md#%E6%B7%B1%E5%BA%A6%E8%BF%81%E7%A7%BB%E5%AD%A6%E4%B9%A0
深度对抗迁移迁移学习 Deep Adversarial transfer learninghttps://github.com/jindongwang/transferlearning/blob/master/doc/awesome_paper.md#%E5%AF%B9%E6%8A%97%E8%BF%81%E7%A7%BB%E5%AD%A6%E4%B9%A0
传递迁移学习 Transitive Transfer Learninghttps://github.com/jindongwang/transferlearning/blob/master/doc/awesome_paper.md#%E4%BC%A0%E9%80%92%E8%BF%81%E7%A7%BB%E5%AD%A6%E4%B9%A0
强化迁移学习 Transfer Learning with Reinforcement Learninghttps://github.com/jindongwang/transferlearning/blob/master/doc/awesome_paper.md#%E5%BC%BA%E5%8C%96%E8%BF%81%E7%A7%BB%E5%AD%A6%E4%B9%A0
应用 Applicationshttps://github.com/jindongwang/transferlearning/blob/master/doc/awesome_paper.md#%E5%BA%94%E7%94%A8
迁移学习用于行为识别 Transfer learning for 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
paperweeklyhttp://www.paperweekly.site/collections/231/papers
https://github.com/wayne980/transferlearning#3theory-and-survey
A survey on transfer learninghttp://ieeexplore.ieee.org/abstract/document/5288526/
Analysis of Representations for Domain Adaptationhttps://dl.acm.org/citation.cfm?id=2976474
A Theory of Learning from Different Domainshttps://link.springer.com/article/10.1007/s10994-009-5152-4
Learning Bounds for Domain Adaptationhttp://papers.nips.cc/paper/3212-learning-bounds-for-domain-adaptation
A Hilbert Space Embedding for Distributionshttps://link.springer.com/chapter/10.1007/978-3-540-75225-7_5
A Kernel Two-Sample Testhttp://www.jmlr.org/papers/v13/gretton12a.html
Optimal kernel choice for large-scale two-sample testshttp://papers.nips.cc/paper/4727-optimal-kernel-choice-for-large-scale-two-sample-tests
Matlabhttps://github.com/lopezpaz/classifier_tests/tree/master/code/unit_test_mmd
Pythonhttps://github.com/jindongwang/transferlearning/tree/master/code/basic/mmd.py
Transfer Metric Learning: Algorithms, Applications and Outlookshttps://arxiv.org/abs/1810.03944
Asymmetric Heterogeneous Transfer Learning: A Surveyhttps://arxiv.org/abs/1804.10834
Neural Style Transfer: A Reviewhttps://arxiv.org/abs/1705.04058
Deep Visual Domain Adaptation: A Surveyhttps://www.sciencedirect.com/science/article/pii/S0925231218306684
A survey on multi-task learninghttps://arxiv.org/abs/1707.08114
A survey on heterogeneous transfer learninghttps://link.springer.com/article/10.1186/s40537-017-0089-0
Cross-dataset recognition: a surveyhttps://arxiv.org/abs/1705.04396
A survey of transfer learninghttps://pan.baidu.com/s/1gfgXLXT
迁移学习研究进展https://pan.baidu.com/s/1bpautob
Visual Domain Adaptation: A Survey of Recent Advanceshttps://pan.baidu.com/s/1o8BR7Vc
Transfer Learning for Activity Recognition: A Surveyhttps://pan.baidu.com/s/1kVABOYr
Transfer Learning for Reinforcement Learning Domains: A Surveyhttps://pan.baidu.com/s/1slfr0w1
A Survey of Multi-source Domain Adaptationhttps://pan.baidu.com/s/1eSGREF4
https://github.com/wayne980/transferlearning#4code
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https://github.com/wayne980/transferlearning#5transfer-learning-scholars
这里https://github.com/jindongwang/transferlearning/blob/master/doc/scholar_TL.md
herehttps://github.com/jindongwang/transferlearning/blob/master/doc/scholar_TL.md
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/
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Boqing Gonghttp://boqinggong.info/index.html
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Fuzhen Zhuanghttp://www.intsci.ac.cn/users/zhuangfuzhen/
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Mingsheng Longhttp://ise.thss.tsinghua.edu.cn/~mlong/
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Weike Panhttps://sites.google.com/site/weikep/
Google Scholarhttps://scholar.google.com/citations?user=pC5Q26MAAAAJ&hl=en
Tongliang Liuhttp://ieeexplore.ieee.org/abstract/document/8259375/
Google scholarhttps://scholar.google.com.hk/citations?hl=zh-CN&user=EiLdZ_YAAAAJ
Tatiana Tommasihttp://tatianatommasi.wixsite.com/tatianatommasi/3
https://github.com/wayne980/transferlearning#6transfer-learning-thesis
Correlation Alignment for Domain Adaptationhttp://www.cs.uml.edu/~bsun/papers/baochen_phd_thesis.pdf
Kernel Methods for Unsupervised Domain Adaptationhttps://pan.baidu.com/s/1bpbawv9
迁移学习问题与方法研究http://ise.thss.tsinghua.edu.cn/~mlong/doc/phd-thesis-mingsheng-long.pdf
自适应行为识别中的迁移学习方法研究https://pan.baidu.com/s/1kVqYXnh
Learning based Activity Recognitionhttps://pan.baidu.com/s/1bp2K9HX
Learning with Limited Data in Sensor-based Human Behavior Predictionhttps://pan.baidu.com/s/1o8MbbBk
Feature-based Transfer Learning and Its Applicationshttps://pan.baidu.com/s/1bUqMfW
基于实例和特征的迁移学习算法研究https://pan.baidu.com/s/1i4Vyygd
完整版https://pan.baidu.com/s/1bqXEASn
https://github.com/wayne980/transferlearning#7datasets-and-benchmarks
HEREhttps://github.com/jindongwang/transferlearning/blob/master/data
这里https://github.com/jindongwang/transferlearning/blob/master/data
https://github.com/wayne980/transferlearning#8transfer-learning-challenges
Visual Domain Adaptation Challenge (VisDA)http://ai.bu.edu/visda-2018/
https://github.com/wayne980/transferlearning#applications
HEREhttps://github.com/jindongwang/transferlearning/blob/master/doc/transfer_learning_application.md
这里https://github.com/jindongwang/transferlearning/blob/master/doc/transfer_learning_application.md
https://github.com/wayne980/transferlearning#other-resources
Transfer Learning for Multimedia Applications(A Special Issue on Multimedia Tools and Applications (MTAP))https://lijin118.github.io/mtap/
A semi-supervised domain adaptation libraryhttps://domainadaptation.org
https://github.com/wayne980/transferlearning#contributing
HEREhttps://github.com/jindongwang/transferlearning/blob/master/CONTRIBUTING.md
transferlearning.xyz/http://transferlearning.xyz/
Readme https://github.com/wayne980/transferlearning#readme-ov-file
MIT license https://github.com/wayne980/transferlearning#MIT-1-ov-file
Contributing https://github.com/wayne980/transferlearning#contributing-ov-file
Please reload this pagehttps://github.com/wayne980/transferlearning
Activityhttps://github.com/wayne980/transferlearning/activity
0 forkshttps://github.com/wayne980/transferlearning/forks
Report repository https://github.com/contact/report-content?content_url=https%3A%2F%2Fgithub.com%2Fwayne980%2Ftransferlearning&report=wayne980+%28user%29
Releaseshttps://github.com/wayne980/transferlearning/releases
Packages 0https://github.com/users/wayne980/packages?repo_name=transferlearning
Please reload this pagehttps://github.com/wayne980/transferlearning
Contributorshttps://github.com/wayne980/transferlearning/graphs/contributors
Please reload this pagehttps://github.com/wayne980/transferlearning
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