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社区首页 >专栏 >机器学习各领域必读经典综述

机器学习各领域必读经典综述

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zenRRan
发布2020-09-30 11:27:34
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发布2020-09-30 11:27:34
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文章被收录于专栏:深度学习自然语言处理

来自 | Github

整理 | 深度学习这件小事

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。

资源链接:https://github.com/eugeneyan/ml-surveys

目录

  • Recommendation
  • Deep Learning
  • Natural Language Processing
  • Computer Vision
  • Reinforcement Learning
  • Embeddings
  • Meta-learning and Few-shot Learning
  • Others

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
  • Graph: A Comprehensive Survey on Graph Neural Networks

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
  • Transformers: Efficient Transformers: A Survey
  • 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
  • Image Captioning: A Comprehensive Survey of Deep Learning for Image Captioning

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
  • Text: A Reproducible Survey on Word Embeddings and Ontology-based Methods for Word Similarity

迁移学习

  • Transfer learning: A Survey on Transfer Learning
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原始发表:2020-09-27,如有侵权请联系 cloudcommunity@tencent.com 删除

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