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Everything about Transfer Learning. 迁移学习.

Papers • Tutorials • Research areas • Theory • Survey • Code • Dataset & benchmark

Thesis • Scholars • Contests • Journal/conference • Applications • Others • Contributing

Widely used by top conferences and journals: - Conferences: [CVPR'22] [NeurIPS'21] [IJCAI'21] [ESEC/FSE'20] [IJCNN'20] [ACMMM'18] [ICME'19] - Journals: [IEEE TKDE] [ACM TIST] [Information sciences] [Neurocomputing] [IEEE Transactions on Cognitive and Developmental Systems]

@Misc{transferlearning.xyz,
howpublished = {\url{http://transferlearning.xyz}},   
title = {Everything about Transfer Learning and Domain Adapation},  
author = {Wang, Jindong and others}  
}  

Related Codes: - Large language model evaluation: [llm-eval] - Large language model enhancement: [llm-enhance] - Robust machine learning: [robustlearn: robust machine learning] - Semi-supervised learning: [USB: unified semi-supervised learning benchmark] | [TorchSSL: a unified SSL library] - LLM benchmark: [PromptBench: adversarial robustness of prompts of LLMs] - Federated learning: [PersonalizedFL: library for personalized federated learning] - Activity recognition and machine learning [Activity recognition]｜[Machine learning]

NOTE: You can directly open the code in Gihub Codespaces on the web to run them without downloading! Also, try github.dev.

0.Papers (论文)

Awesome transfer learning papers (迁移学习文章汇总)

• Paperweekly: A website to recommend and read paper notes

Latest papers:

• By topic: doc/awesome_papers.md
• By date: doc/awesome_paper_date.md

Updated at 2024-02-18:

• Simulations of Common Unsupervised Domain Adaptation Algorithms for Image Classification [arxiv]

• Unsupervised domain adaptaiton for image classification

• Semantics-aware Test-time Adaptation for 3D Human Pose Estimation [arxiv]

• Test-time adaptation for3D human pose estimation

• Transfer Learning of CATE with Kernel Ridge Regression [arxiv]

• Transfer learning with kernel ridge regression

• Why Domain Generalization Fail? A View of Necessity and Sufficiency [arxiv]

• Analyze why domain generalization fail from the view of necessity and sufficiency

Updated at 2024-02-11:

• Beyond Batch Learning: Global Awareness Enhanced Domain Adaptation [arxiv]
• Global awareness for enhanced domain adaptation

1.Introduction and Tutorials (简介与教程)

Want to quickly learn transfer learning？想尽快入门迁移学习？看下面的教程。

• Books 书籍
• Introduction to Transfer Learning: Algorithms and Practice [Buy or read]
• 《迁移学习》（杨强） [Buy] [English version]

• 《迁移学习导论》(王晋东、陈益强著) [Homepage] [Buy]

• Blogs 博客

• Zhihu blogs - 知乎专栏《小王爱迁移》系列文章

• Video tutorials 视频教程

• Transfer learning 迁移学习:
  • Recent advance of transfer learning - 2022年最新迁移学习发展现状探讨
  • Definitions of transfer learning area - 迁移学习领域名词解释 [Article]
  • Transfer learning by Hung-yi Lee @ NTU - 台湾大学李宏毅的视频讲解(中文视频)
• Domain generalization 领域泛化：
  • IJCAI-ECAI'22 tutorial on domain generalization - 领域泛化tutorial
  • Domain generalization - 迁移学习新兴研究方向领域泛化

• Domain adaptation 领域自适应：

  • Domain adaptation - 迁移学习中的领域自适应方法(中文)

• Brief introduction and slides 简介与ppt资料

• Recent advance of transfer learning
• Domain generalization survey
• Brief introduction in Chinese
  • PPT (English) | PPT (中文)
• 迁移学习中的领域自适应方法 Domain adaptation: PDF ｜ Video on Bilibili | Video on Youtube

• Tutorial on transfer learning by Qiang Yang: IJCAI'13 | 2016 version

• Talk is cheap, show me the code 动手教程、代码、数据

• Pytorch tutorial on transfer learning

  • Pytorch finetune
  • DeepDA: a unified deep domain adaptation toolbox
  • DeepDG: a unified deep domain generalization toolbox
  • 更多 More...

• 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

• Negative transfer - 负迁移

2.Transfer Learning Areas and Papers (研究领域与相关论文)

• Survey
• Theory
• Per-training/Finetuning
• Knowledge distillation
• Traditional domain adaptation
• Deep domain adaptation
• Domain generalization
• Source-free domain adaptation
• Multi-source domain adaptation
• Heterogeneous transfer learning
• Online transfer learning
• Zero-shot / few-shot learning
• Multi-task learning
• Transfer reinforcement learning
• Transfer metric learning
• Federated transfer learning
• Lifelong transfer learning
• Safe transfer learning
• Transfer learning applications

3.Theory and Survey (理论与综述)

Here are some articles on transfer learning theory and survey.

Survey (综述文章)：

• 2023 Source-Free Unsupervised Domain Adaptation: A Survey [arxiv]
• 2022 Transfer Learning for Future Wireless Networks: A Comprehensive Survey
• 2022 A Review of Deep Transfer Learning and Recent Advancements
• 2022 Transferability in Deep Learning: A Survey, from Mingsheng Long in THU.
• 2021 Domain generalization: IJCAI-21 Generalizing to Unseen Domains: A Survey on Domain Generalization | 知乎文章 | 微信公众号
• First survey on domain generalization
• 第一篇对Domain generalization (领域泛化)的综述
• 2021 Vision-based activity recognition: A Survey of Vision-Based Transfer Learning in Human Activity Recognition
• 2021 ICSAI A State-of-the-Art Survey of Transfer Learning in Structural Health Monitoring
• 2020 Transfer learning: survey and classification, Advances in Intelligent Systems and Computing.
• 2020 迁移学习最新survey，来自中科院计算所庄福振团队，发表在Proceedings of the IEEE: A Comprehensive Survey on Transfer Learning
• 2020 负迁移的综述：Overcoming Negative Transfer: A Survey
• 2020 知识蒸馏的综述: Knowledge Distillation: A Survey
• 用transfer learning进行sentiment classification的综述：A Survey of Sentiment Analysis Based on Transfer Learning
• 2019 一篇新survey：Transfer Adaptation Learning: A Decade Survey
• 2018 一篇迁移度量学习的综述: Transfer Metric Learning: Algorithms, Applications and Outlooks
• 2018 一篇最近的非对称情况下的异构迁移学习综述：Asymmetric Heterogeneous Transfer Learning: A Survey
• 2018 Neural style transfer的一个survey：Neural Style Transfer: A Review
• 2018 深度domain adaptation的一个综述：Deep Visual Domain Adaptation: A Survey
• 2017 多任务学习的综述，来自香港科技大学杨强团队：A survey on multi-task learning
• 2017 异构迁移学习的综述：A survey on heterogeneous transfer learning
• 2017 跨领域数据识别的综述：[Cross-dataset recognition: a survey](https://arxiv.org/abs/1705.0