机器学习是一门多领域交叉学科，涉及概率论、统计学、逼近论、凸分析、算法复杂度理论等多门学科。专门研究计算机怎样模拟或实现人类的学习行为，以获取新的知识或技能，重新组织已有的知识结构使之不断改善自身的性能。
机器学习及其相关领域，如深度学习、自然语言处理、计算机视觉、推荐系统、强化学习等领域最近几年非常火，每年各式各样的国际顶会，投稿数每年都会海量增加。要持续Follow这些领域最新的技术，刷遍各大会议最新会议非常费时费力，特别是对于刚入门的同学。因此，为了方便同学们了解机器学习、AI各领域的最新的技术全貌，本资源整理了各领域必读的经典综述论文，分享给大家。
资源整理自网络，源地址：https://github.com/eugeneyan/ml-surveys
目录
推荐系统
Algorithms: Recommender systems survey
Algorithms: Deep Learning based Recommender System: A Survey and New Perspectives
Algorithms: Are We Really Making Progress? A Worrying Analysis of Neural Recommendation Approaches
Serendipity: A Survey of Serendipity in Recommender Systems
Diversity: Diversity in Recommender Systems – A survey
Explanations: A Survey of Explanations in Recommender Systems
深度学习
Architecture: A State-of-the-Art Survey on Deep Learning Theory and Architectures
Knowledge distillation: Knowledge Distillation: A Survey
Model compression: Compression of Deep Learning Models for Text: A Survey
Transfer learning: A Survey on Deep Transfer Learning
Neural architecture search: A Comprehensive Survey of Neural Architecture Search-- Challenges and Solutions
Neural architecture search: Neural Architecture Search: A Survey
自然语言处理
Deep Learning: Recent Trends in Deep Learning Based Natural Language Processing
Classification: Deep Learning Based Text Classification: A Comprehensive Review
Generation: Survey of the SOTA in Natural Language Generation: Core tasks, applications and evaluation
Generation: Neural Language Generation: Formulation, Methods, and Evaluation
Transfer learning: Exploring Transfer Learning with T5: the Text-To-Text Transfer Transformer (Paper)
Metrics: Beyond Accuracy: Behavioral Testing of NLP Models with CheckList
Metrics: Evaluation of Text Generation: A Survey
计算机视觉
Object detection: Object Detection in 20 Years
Adversarial attacks: Threat of Adversarial Attacks on Deep Learning in Computer Vision
Autonomous vehicles: Computer Vision for Autonomous Vehicles: Problems, Datasets and State of the Art
深度强化学习
Algorithms: A Brief Survey of Deep Reinforcement Learning
Transfer learning: Transfer Learning for Reinforcement Learning Domains
Economics: Review of Deep Reinforcement Learning Methods and Applications in Economics
向量化技术
Graph: A Comprehensive Survey of Graph Embedding: Problems, Techniques and Applications
Text: From Word to Sense Embeddings:A Survey on Vector Representations of Meaning
Text: Diachronic Word Embeddings and Semantic Shifts
Text: Word Embeddings: A Survey
Meta-learning and Few-shot Learning
NLP: Meta-learning for Few-shot Natural Language Processing: A Survey
Domain Agnostic: Learning from Few Samples: A Survey
NN: Meta-Learning in Neural Networks: A Survey
Domain Agnostic: A Comprehensive Overview and Survey of Recent Advances in Meta-Learning
Domain Agnostic: Baby steps towards few-shot learning with multiple semantics
Domain Agnostic: Meta-Learning: A Survey
Domain Agnostic: A Perspective View And Survey Of Meta-learning
迁移学习
Transfer learning: A Survey on Transfer Learning
