ICLR 2020 元學習（Meta-learning）及小樣本學習（Few-shot learning)等方向上接收論文總結

ICLR 2020 將於2020年4 月 26 日於埃塞俄比亞首都亞的斯亞貝巴舉行。

在最終提交的 2594 篇論文中，有 687 篇被接收，接收率爲 26.5%；和之前一樣，所有被接收的論文都將進行 poster 展示；23% 的接收論文將進行口頭講述報告，其中108 篇論文爲 spotlight，演講時間 4 分鐘，48 篇論文將進行 10 分鐘以上的 talk。

對ICLR 2020接收論文中與元學習（Meta-learning）及小樣本學習（few-shot learning）相關方向的論文進行總結。若有遺漏或其他錯誤還請指正。

元學習（Meta-learning）

1. Learning To Balance: Bayesian Meta-learning For Imbalanced And Out-of-distribution Tasks (Talk)
2. Meta-learning With Warped Gradient Descent (Talk)
3. Meta-learning Without Memorization (Spotlight)
4. Meta-learning Acquisition Functions For Transfer Learning In Bayesian Optimization (Spotlight)
5. Automated Relational Meta-learning (Poster)
6. Empirical Bayes Transductive Meta-learning With Synthetic Gradients (Poster)
7. Meta-learning Curiosity Algorithms (Poster)
8. Towards Fast Adaptation Of Neural Architectures With Meta Learning (Poster)
9. Differentially Private Meta-learning (Poster)
10. Meta-learning Deep Energy-based Memory Models (Poster)
11. Varibad: A Very Good Method For Bayes-adaptive Deep Rl Via Meta-learning (Poster)
12. ES-MAML: Simple Hessian-Free Meta Learning (Poster)
13. Watch, Try, Learn: Meta-learning From Demonstrations And Rewards (Poster)

Meta Reinforcement Learning

1. Meta-Q-Learning (Talk)
2. Improving Generalization In Meta Reinforcement Learning Using Neural Objectives (Spotlight)
3. Meta Reinforcement Learning With Autonomous Inference Of Subtask Dependencies (Poster)

小樣本學習（Few-shot Learning）

1. A Theoretical Analysis Of The Number Of Shots In Few-shot Learning (Poster)
2. A Baseline For Few-shot Image Classification (Poster)
3. Metapix: Few-shot Video Retargeting (Poster)
4. Cross-domain Few-shot Classification Via Learned Feature-wise Transformation (Spotlight)
5. Few-shot Learning On Graphs Via Super-classes Based On Graph Spectral Measures (Poster)
6. Few-shot Text Classification With Distributional Signatures (Poster)
7. Meta-dataset: A Dataset Of Datasets For Learning To Learn From Few Examples (Poster)

Zero-shot Learning

1. Locality And Compositionality In Zero-shot Learning (Poster)

參考資料：

1. https://openreview.net/group?id=ICLR.cc/2020/Conference
2. https://github.com/shaohua0116/ICLR2020-OpenReviewData#Data
3. https://chillee.github.io/OpenReviewExplorer/