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 751–775 of 3073 papers

Title	Date	Tasks	Status	Score
Active Labeling: Streaming Stochastic Gradients	May 26, 2022	Active Learningregression	CodeCode Available	5
Advancing African-Accented Speech Recognition: Epistemic Uncertainty-Driven Data Selection for Generalizable ASR Models	Jun 3, 2023	Accented Speech RecognitionActive Learning	CodeCode Available	5
Interactively Teaching an Inverse Reinforcement Learner with Limited Feedback	Sep 16, 2023	Active LearningDecision Making	CodeCode Available	5
Interactive Refinement of Cross-Lingual Word Embeddings	Nov 8, 2019	Active LearningCross-Lingual Word Embeddings	CodeCode Available	5
Anytime Active Learning	Jul 27, 2014	Active LearningDocument Classification	CodeCode Available	5
Active Learning of Molecular Data for Task-Specific Objectives	Aug 20, 2024	Active LearningGaussian Processes	CodeCode Available	5
A-Optimal Active Learning	Oct 18, 2021	Active LearningExperimental Design	CodeCode Available	5
LSCALE: Latent Space Clustering-Based Active Learning for Node Classification	Dec 13, 2020	Active LearningClustering	CodeCode Available	5
Benchmarking of Query Strategies: Towards Future Deep Active Learning	Dec 10, 2023	Active LearningBenchmarking	CodeCode Available	5
An Active Learning Reliability Method for Systems with Partially Defined Performance Functions	Oct 5, 2022	Active LearningAutonomous Driving	CodeCode Available	5
Bayesian Semi-supervised Learning with Graph Gaussian Processes	Sep 12, 2018	Active LearningGaussian Processes	CodeCode Available	5
Iterative Projection and Matching: Finding Structure-preserving Representatives and Its Application to Computer Vision	Nov 29, 2018	Action RecognitionActive Learning	CodeCode Available	5
Black-Box Batch Active Learning for Regression	Feb 17, 2023	Active Learningregression	CodeCode Available	5
Active Keyword Selection to Track Evolving Topics on Twitter	Sep 22, 2022	Active Learning	CodeCode Available	5
Knowledge-driven Active Learning	Oct 15, 2021	Active LearningMulti-Label Classification	CodeCode Available	5
Approximate Bayesian Computation with Domain Expert in the Loop	Jan 28, 2022	Active LearningDimensionality Reduction	CodeCode Available	5
A Practical Incremental Learning Framework For Sparse Entity Extraction	Jun 26, 2018	Active LearningEntity Extraction using GAN	CodeCode Available	5
A3: Active Adversarial Alignment for Source-Free Domain Adaptation	Sep 27, 2024	Active LearningDomain Adaptation	CodeCode Available	5
A Bayesian Approach for Sequence Tagging with Crowds	Nov 2, 2018	Active LearningArgument Mining	CodeCode Available	5
Active Learning for Neural Machine Translation	Dec 30, 2022	Active LearningMachine Translation	CodeCode Available	5
Learning How to Active Learn by Dreaming	Jul 1, 2019	Active Learningnamed-entity-recognition	CodeCode Available	5
Learning How to Actively Learn: A Deep Imitation Learning Approach	Jul 1, 2018	Active LearningGeneral Classification	CodeCode Available	5
Active Learning of Spin Network Models	Mar 25, 2019	Active Learning	CodeCode Available	5
Architectural and Inferential Inductive Biases For Exchangeable Sequence Modeling	Mar 3, 2025	Active LearningDecision Making	CodeCode Available	5
Bayesian Dark Knowledge	Jun 14, 2015	Active Learningparameter estimation	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