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 151–175 of 3073 papers

Title	Date	Tasks	Status	Hype
Active Imitation Learning with Noisy Guidance	May 26, 2020	Active LearningImitation Learning	CodeCode Available	1
AfroLM: A Self-Active Learning-based Multilingual Pretrained Language Model for 23 African Languages	Nov 7, 2022	Active LearningLanguage Modeling	CodeCode Available	1
Active Bayesian Causal Inference	Jun 4, 2022	Active LearningCausal Discovery	CodeCode Available	1
A Holistic Approach to Undesired Content Detection in the Real World	Aug 5, 2022	Active Learning	CodeCode Available	1
AL-GTD: Deep Active Learning for Gaze Target Detection	Sep 27, 2024	Active Learning	CodeCode Available	1
A-LINK: Recognizing Disguised Faces via Active Learning based Inter-Domain Knowledge	Sep 23, 2019	Active LearningDomain Adaptation	CodeCode Available	1
Active Learning Helps Pretrained Models Learn the Intended Task	Apr 18, 2022	Active Learning	CodeCode Available	1
Active Learning at the ImageNet Scale	Nov 25, 2021	Active Learning	CodeCode Available	1
ASGN: An Active Semi-supervised Graph Neural Network for Molecular Property Prediction	Jul 7, 2020	Active LearningGraph Neural Network	CodeCode Available	1
Stochastic Batch Acquisition: A Simple Baseline for Deep Active Learning	Jun 22, 2021	Active Learning	CodeCode Available	1
Open Source Software for Efficient and Transparent Reviews	Jun 22, 2020	Active LearningBIG-bench Machine Learning	CodeCode Available	1
Active learning based generative design for the discovery of wide bandgap materials	Feb 28, 2021	Active LearningBand Gap	CodeCode Available	1
A Survey of Dataset Refinement for Problems in Computer Vision Datasets	Oct 21, 2022	Active Learning	CodeCode Available	1
AcTune: Uncertainty-aware Active Self-Training for Semi-Supervised Active Learning with Pretrained Language Models	Dec 16, 2021	Active LearningLanguage Modeling	CodeCode Available	1
A unified framework for closed-form nonparametric regression, classification, preference and mixed problems with Skew Gaussian Processes	Dec 12, 2020	Active LearningBinary Classification	CodeCode Available	1
Bamboo: Building Mega-Scale Vision Dataset Continually with Human-Machine Synergy	Mar 15, 2022	Active LearningClassification	CodeCode Available	1
Bayesian Model-Agnostic Meta-Learning	Jun 11, 2018	Active Learningimage-classification	CodeCode Available	1
Bayesian Optimization with Conformal Prediction Sets	Oct 22, 2022	Active LearningBayesian Optimization	CodeCode Available	1
BenchPress: A Deep Active Benchmark Generator	Aug 13, 2022	Active LearningCPU	CodeCode Available	1
Biological Sequence Design with GFlowNets	Mar 2, 2022	Active LearningDiversity	CodeCode Available	1
Active Learning by Acquiring Contrastive Examples	Sep 8, 2021	Active LearningDiversity	CodeCode Available	1
Active Learning by Feature Mixing	Mar 14, 2022	Active Learning	CodeCode Available	1
Building a Scalable and Interpretable Bayesian Deep Learning Framework for Quality Control of Free Form Surfaces	Apr 7, 1994	Active LearningBenchmarking	CodeCode Available	1
Can Active Learning Preemptively Mitigate Fairness Issues?	Apr 14, 2021	Active LearningFairness	CodeCode Available	1
Active Learning for Open-set Annotation	Jan 18, 2022	Active Learning	CodeCode Available	1

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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