ml-surveys
It's hard to keep up with the latest and greatest in machine learning. Here's a selection of survey papers summarizing the advances in the field.
Figuring out how to implement your ML project? Learn how other organizations did it applied-ml
Table of Contents
- Recommendation
- Deep Learning
- Natural Language Processing
- Computer Vision
- Reinforcement Learning
- Embeddings
- Others
Recommendation
- 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 โ A survey
- Explanations: A Survey of Explanations in Recommender Systems
Deep Learning
- Architecture: A State-of-the-Art Survey on Deep Learning Theory and Architectures
- Knowledge distillation: Knowledge Distillation: A Survey
- Transfer learning: A Survey on Deep Transfer Learning
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
Computer Vision
- 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
Reinforcement Learning
- Algorithms: A Brief Survey of Deep Reinforcement Learning
- Transfer learning: Transfer Learning for Reinforcement Learning Domains
Embeddings
- 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
Others
- Transfer learning: A Survey on Transfer Learning