| Year | Title | Author | Publication | Code | Tasks | Notes | Datasets | Notions |
|---|---|---|---|---|---|---|---|---|
| 2019 | Active Learning for Probabilistic Structured Prediction of Cuts and Matchings | Behpour et al. | ICML | code | multi-label classification and object tracking | Uncertainty, SVMs, adversarial, Tra, Hard |
Bibtex, Bookmarks, CAL500, Core15k, Enron, NUS-WIDE, TMC2007, Yeast | |
| 2019 | Active Learning with Disagreement Graphs | Cortes et al. | ICML | - | Classification | Disagreement Graphs, BNNs, None, Tra, Hard |
UCI repository: nomao, codrna, skin, covtype | |
| 2019 | Fast Direct Search in an Optimally Compressed Continuous Target Space for Efficient Multi-Label Active Learning | Shi and Yu | ICML | code | multi-label classification | Uncertainty, Gaussian Process , None, Tra, Hard |
Delicious, BookMark, WebAPI, Core15K, Bibtex | |
| 2019 | Active Learning for Decision-Making from Imbalanced Observational Data | Sundin et al. | ICML | code | decision-making task | Estimated reliability, BNNs, None, Tra, Hard |
Synthetic data, IHDP data, Simulated data | |
| 2019 | Bayesian Generative Active Deep Learning | Tran et al. | ICML | code | Image Classification | Generative Active Learning, BNNs , data augmentation, None, Tra, Hard |
MNIST, CIFAR-{10, 100}, and SVHN |