π BibliographyΒΆ
A non-exhaustive list of references for the implemented learning algorithms and query strategies.
Learning AlgorithmsΒΆ
Logistic Regression (LR): Berkson (1944)
k-Nearest Neighbors (kNN): Fix et al. (1952)
Multi-Layer Perceptron (MLP): Werbos (1974)
Naive Bayes (NB): Kononenko (1990)
Support Vector Machine (SVM): Boser et al. (1992)
Random Forest (RF): Breiman (2001)
Extra Trees (ET): Geurts et al. (2006)
XGBoost (XGB): Chen and Guestrin (2016)
CatBoost (CB): Dorogush et al. (2018)
TabNet: Arik and Pfister (2021)
TabPFN: Hollmann et al. (2023)
Query StrategiesΒΆ
Entropy Sampling (ES): Shannon (1948)
Query by Committee (QBC): Seung et al. (1992)
Variance Reduction (VR): Cohn et al. (1993)
Least Confidence (LC): Lewis and Gale (1994)
Margin Sampling (MS): Scheffer et al. (2001)
Expected Error Reduction (EER): Roy & McCallum (2001)
BALD: Houlsby et al. (2011)
Max Entropy (MaxEnt): Gal et al. (2017)
Query by Committee (Variance Ratio): Beluch et al. (2018)
Epistemic Uncertainty Sampling (EUS): Nguyen et al. (2019)
Power Margin Sampling (PowMS): Kirsch et al. (2021)
Min Margin Sampling (MinMS): Jiang et al. (2021)
K-Means: Kang et al. (2004)
CoreSet: Sener & Savarese (2018)
Typical Clustering (TypClust): Hacohen et al. (2022)
FALCUN: Gilhuber et al. (2024)
Cluster Margin Sampling (CluMS): Citovsky et al. (2021)
CLUE: Prabhu et al. (2021)