Active Learning

Active Learning is a paradigm in supervised machine learning which uses fewer training examples to achieve better optimization by iteratively training a predictor, and using the predictor in each iteration to choose the training examples which will increase its chances of finding better configurations and at the same time improving the accuracy of the prediction model

Source: Polystore++: Accelerated Polystore System for Heterogeneous Workloads

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 651–675 of 3073 papers

Title	Date	Tasks	Status	Score
Building a comprehensive syntactic and semantic corpus of Chinese clinical texts	Nov 7, 2016	Active LearningPOS	CodeCode Available	5
Buy Me That Look: An Approach for Recommending Similar Fashion Products	Aug 26, 2020	Active LearningArticles	CodeCode Available	5
Detecting Minority Arguments for Mutual Understanding: A Moderation Tool for the Online Climate Change Debate	Oct 1, 2022	Active Learning	CodeCode Available	5
ALINE: Joint Amortization for Bayesian Inference and Active Data Acquisition	Jun 8, 2025	Active LearningBayesian Inference	CodeCode Available	5
CFlowNets: Continuous Control with Generative Flow Networks	Mar 4, 2023	Active Learningcontinuous-control	CodeCode Available	5
Beyond Marginal Uncertainty: How Accurately can Bayesian Regression Models Estimate Posterior Predictive Correlations?	Nov 6, 2020	Active LearningBenchmarking	CodeCode Available	5
A Little Annotation does a Lot of Good: A Study in Bootstrapping Low-resource Named Entity Recognizers	Aug 23, 2019	Active LearningCross-Lingual Transfer	CodeCode Available	5
Active Learning from Positive and Unlabeled Data	Feb 24, 2016	Active LearningInformativeness	CodeCode Available	5
Active-LATHE: An Active Learning Algorithm for Boosting the Error Exponent for Learning Homogeneous Ising Trees	Oct 27, 2021	Active Learning	CodeCode Available	5
DISCERN: Decoding Systematic Errors in Natural Language for Text Classifiers	Oct 29, 2024	Active Learningtext-classification	CodeCode Available	5
Bidirectional Uncertainty-Based Active Learning for Open Set Annotation	Feb 23, 2024	Active Learning	CodeCode Available	5
Black-Box Batch Active Learning for Regression	Feb 17, 2023	Active Learningregression	CodeCode Available	5
Benchmarking of Query Strategies: Towards Future Deep Active Learning	Dec 10, 2023	Active LearningBenchmarking	CodeCode Available	5
Adaptive Region Selection for Active Learning in Whole Slide Image Semantic Segmentation	Jul 14, 2023	Active LearningInformativeness	CodeCode Available	5
Dissimilar Nodes Improve Graph Active Learning	Dec 5, 2022	Active LearningGraph Embedding	CodeCode Available	5
SoQal: Selective Oracle Questioning for Consistency Based Active Learning of Cardiac Signals	Apr 20, 2020	Active LearningPseudo Label	CodeCode Available	5
Bayesian Semi-supervised Learning with Graph Gaussian Processes	Sep 12, 2018	Active LearningGaussian Processes	CodeCode Available	5
Beyond Labels: Empowering Human Annotators with Natural Language Explanations through a Novel Active-Learning Architecture	May 22, 2023	Active LearningDecision Making	CodeCode Available	5
Boolean matrix logic programming for active learning of gene functions in genome-scale metabolic network models	May 10, 2024	Active LearningExperimental Design	CodeCode Available	5
ALWOD: Active Learning for Weakly-Supervised Object Detection	Sep 14, 2023	Active LearningObject	CodeCode Available	5
Domain-independent Extraction of Scientific Concepts from Research Articles	Jan 9, 2020	Active LearningArticles	CodeCode Available	5
Adaptive Open-Set Active Learning with Distance-Based Out-of-Distribution Detection for Robust Task-Oriented Dialog System	Sep 1, 2024	Active LearningInformativeness	CodeCode Available	5
Bayesian Neural Scaling Laws Extrapolation with Prior-Fitted Networks	May 29, 2025	Active Learning	CodeCode Available	5
Bayesian Dark Knowledge	Jun 14, 2015	Active Learningparameter estimation	CodeCode Available	5
Bayesian Co-navigation: Dynamic Designing of the Materials Digital Twins via Active Learning	Apr 19, 2024	Active Learning	CodeCode Available	5

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Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	TypiClust	Accuracy	93.2	—	Unverified
2	PT4AL	Accuracy	93.1	—	Unverified
3	Learning loss	Accuracy	91.01	—	Unverified
4	CoreGCN	Accuracy	90.7	—	Unverified
5	Core-set	Accuracy	89.92	—	Unverified
6	Random Baseline (Resnet18)	Accuracy	88.45	—	Unverified
7	Random Baseline (VGG16)	Accuracy	85.09	—	Unverified