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 276–300 of 3073 papers

Title	Date	Tasks	Status	Hype	Score
Deep Active Learning for Named Entity Recognition	Jul 19, 2017	Active LearningDecoder	CodeCode Available	1	5
Rethinking the Data Annotation Process for Multi-view 3D Pose Estimation with Active Learning and Self-Training	Dec 27, 2021	3D Pose EstimationActive Learning	CodeCode Available	1	5
DeepAL: Deep Active Learning in Python	Nov 30, 2021	Active Learning	CodeCode Available	1	5
ActiveGLAE: A Benchmark for Deep Active Learning with Transformers	Jun 16, 2023	Active Learning	CodeCode Available	1	5
DeepDrummer : Generating Drum Loops using Deep Learning and a Human in the Loop	Aug 10, 2020	Active LearningEfficient Exploration	CodeCode Available	1	5
Deep Indexed Active Learning for Matching Heterogeneous Entity Representations	Apr 8, 2021	Active LearningBlocking	CodeCode Available	1	5
Detecting Underspecification with Local Ensembles	Oct 21, 2019	Active LearningOut-of-Distribution Detection	CodeCode Available	1	5
Confidence-Aware Learning for Deep Neural Networks	Jul 3, 2020	Active LearningOut-of-Distribution Detection	CodeCode Available	1	5
Enhanced spatio-temporal electric load forecasts using less data with active deep learning	Dec 8, 2020	Active LearningBIG-bench Machine Learning	CodeCode Available	1	5
DIAL: Deep Interactive and Active Learning for Semantic Segmentation in Remote Sensing	Jan 4, 2022	Active LearningSemantic Segmentation	CodeCode Available	1	5
Active Learning for Open-set Annotation	Jan 18, 2022	Active Learning	CodeCode Available	1	5
Creating Custom Event Data Without Dictionaries: A Bag-of-Tricks	Apr 3, 2023	Active LearningQuestion Answering	CodeCode Available	1	5
Accelerating high-throughput virtual screening through molecular pool-based active learning	Dec 13, 2020	Active LearningBayesian Optimization	CodeCode Available	1	5
Divide and Adapt: Active Domain Adaptation via Customized Learning	Jul 21, 2023	Active LearningDomain Adaptation	CodeCode Available	1	5
DEAL: Deep Evidential Active Learning for Image Classification	Jul 22, 2020	Active LearningClassification	CodeCode Available	1	5
Active Surrogate Estimators: An Active Learning Approach to Label-Efficient Model Evaluation	Feb 14, 2022	Active Learning	CodeCode Available	1	5
Active Sensing for Communications by Learning	Dec 8, 2021	Active Learning	CodeCode Available	1	5
Diversity Enhanced Active Learning with Strictly Proper Scoring Rules	Oct 27, 2021	Active LearningDiversity	CodeCode Available	1	5
Active Statistical Inference	Mar 5, 2024	Active Learningvalid	CodeCode Available	1	5
Active Test-Time Adaptation: Theoretical Analyses and An Algorithm	Apr 7, 2024	Active LearningDomain Adaptation	CodeCode Available	1	5
Active Testing: Sample-Efficient Model Evaluation	Mar 9, 2021	Active LearningGaussian Processes	CodeCode Available	1	5
Active Transfer Learning for Efficient Video-Specific Human Pose Estimation	Nov 8, 2023	Active LearningPose Estimation	CodeCode Available	1	5
Evidential Uncertainty Quantification: A Variance-Based Perspective	Nov 19, 2023	Active LearningClassification	CodeCode Available	1	5
Active Anomaly Detection via Ensembles	Sep 17, 2018	Active LearningAnomaly Detection	CodeCode Available	1	5
Fluent: An AI Augmented Writing Tool for People who Stutter	Aug 23, 2021	Active Learning	CodeCode Available	1	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