| Year | Title | Author | Publication | Code | Tasks | Notes | Datasets | Notions |
|---|---|---|---|---|---|---|---|---|
| 2020 | The Power of Comparisons for Actively Learning Linear Classifiers | Hopkins et al. | NIPS | - | Linear Classifiers |
All, Bayesian, Reliable and Probably Useful (RPU) learning, Tra,Hard |
Give low bound |
|
| 2020 | Efficient active learning of sparse halfspaces with arbitrary bounded noise | Zhang et al. | NIPS | - | linear classifiers (halfspaces) |
we substantially improve on the state-of-the-art results on efficient active learning of sparse halfspaces under bounded noise. Furthermore, our new interpretation of online learning regret inequalities could lead to new designs of other efficient learning algorithms. | ||
| 2020 | Finding the Homology of Decision Boundaries with Active Learning | Li et al. | NIPS | code | Image Classification |
decision boundary,classifier,Meta-Learning,Tra,Hard |
Banknote, MNIST, CIFAR10 | |
| 2020 | Graph Policy Network for Transferable Active Learning on Graphs | Hu et al. | NIPS | - | Node Classification |
Influence, Graph Policy Network, Reinforce learning, Tr, Hard |
Reddit， Cora, Citeseer and Pubmed, Coauthor-Physics and Coauthor-CS | |
| 2020 | Deep active inference agents using Monte-Carlo methods | Fountas et al. | NIPS | code | Active inference |
Monte-Carlo (MC) sampling,Bayesian Framework,None, Tra, Hard |
dSprites dataset | |
| 2020 | Exemplar Guided Active Learning | Hartford et al. | NIPS | - | multi-class logistic regression classifier |
hybrid,BERT, None, Pre-training+Fine-tuning,Hard |
Reddit word sense disambiguation dataset |