小样本学习论文总结（few-shot learning）

2015

1. Koch, Gregory, Richard Zemel, and Ruslan Salakhutdinov. "Siamese neural networks for one-shot image recognition." ICML Deep Learning Workshop. Vol. 2. 2015. [paper]

2016

1. Ravi, Sachin, and Hugo Larochelle. "Optimization as a model for few-shot learning." (2016). [paper]
2. Santoro, Adam, et al. "Meta-learning with memory-augmented neural networks." International conference on machine learning. 2016.[paper]
3. Xie, Ruobing, et al. "Representation learning of knowledge graphs with entity descriptions." Thirtieth AAAI Conference on Artificial Intelligence. 2016. [paper]
4. Ma, Yukun, Erik Cambria, and Sa Gao. "Label embedding for zero-shot fine-grained named entity typing." Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers. 2016.[paper]
5. Vinyals, Oriol, et al. "Matching networks for one shot learning." Advances in neural information processing systems. 2016.[paper]

2017

1. Garcia, Victor, and Joan Bruna. "Few-shot learning with graph neural networks." arXiv preprint arXiv:1711.04043 (2017).[paper]
2. Snell, Jake, Kevin Swersky, and Richard Zemel. "Prototypical networks for few-shot learning." Advances in Neural Information Processing Systems. 2017. [paper]
3. Finn, Chelsea, Pieter Abbeel, and Sergey Levine. "Model-agnostic meta-learning for fast adaptation of deep networks." Proceedings of the 34th International Conference on Machine Learning-Volume 70. JMLR. org, 2017.[paper]
4. Munkhdalai, Tsendsuren, and Hong Yu. "Meta networks." Proceedings of the 34th International Conference on Machine Learning-Volume 70. JMLR. org, 2017.[paper]
5. Mishra, Nikhil, et al. "A simple neural attentive meta-learner." arXiv preprint arXiv:1707.03141 (2017).[paper]

2018

1. Yu, Mo, et al. "Diverse few-shot text classification with multiple metrics." arXiv preprint arXiv:1805.07513 (2018).[paper]