SOTAVerified

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 AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 351–400 of 3073 papers

TitleStatusHype
Deep Active Learning with Adaptive AcquisitionCode0
ActiveEA: Active Learning for Neural Entity AlignmentCode0
Active Learning for Derivative-Based Global Sensitivity Analysis with Gaussian ProcessesCode0
Deep Active Learning with a Neural Architecture SearchCode0
Deeper Connections between Neural Networks and Gaussian Processes Speed-up Active LearningCode0
DistALANER: Distantly Supervised Active Learning Augmented Named Entity Recognition in the Open Source Software EcosystemCode0
A Cross-Domain Benchmark for Active LearningCode0
Active DOP: A constituency treebank annotation tool with online learningCode0
Data-efficient Neural Text Compression with Interactive LearningCode0
Data Lifecycle Management in Evolving Input Distributions for Learning-based Aerospace ApplicationsCode0
ABC3: Active Bayesian Causal Inference with Cohn Criteria in Randomized ExperimentsCode0
Active Learning for Deep Gaussian Process SurrogatesCode0
Deep Active Alignment of Knowledge Graph Entities and SchemataCode0
Active Learning for Deep Detection Neural NetworksCode0
Active Learning for Decision-Making from Imbalanced Observational DataCode0
Curiosity Driven Exploration to Optimize Structure-Property Learning in MicroscopyCode0
Automated Progressive Red TeamingCode0
Data augmentation on-the-fly and active learning in data stream classificationCode0
Crowd Counting With Partial Annotations in an ImageCode0
Crowd-Powered Photo Enhancement Featuring an Active Learning Based Local FilterCode0
Active Diffusion and VCA-Assisted Image Segmentation of Hyperspectral ImagesCode0
Cross-layer Optimization for High Speed Adders: A Pareto Driven Machine Learning ApproachCode0
CrudeOilNews: An Annotated Crude Oil News Corpus for Event ExtractionCode0
Deep Active Audio Feature Learning in Resource-Constrained EnvironmentsCode0
covEcho Resource constrained lung ultrasound image analysis tool for faster triaging and active learningCode0
Cost-Sensitive Active Learning for Incomplete DataCode0
Cost-Sensitive Reference Pair Encoding for Multi-Label LearningCode0
Cost-Effective Active Learning for Melanoma SegmentationCode0
Cost Effective Active SearchCode0
Active Learning for Classifying 2D Grid-Based Level CompletabilityCode0
ActiveHARNet: Towards On-Device Deep Bayesian Active Learning for Human Activity RecognitionCode0
Cost-Accuracy Aware Adaptive Labeling for Active LearningCode0
Cost-Effective Active Learning for Deep Image ClassificationCode0
Cost-effective Object Detection: Active Sample Mining with Switchable Selection CriteriaCode0
Controllable Textual Inversion for Personalized Text-to-Image GenerationCode0
Continual Deep Active Learning for Medical Imaging: Replay-Base Architecture for Context AdaptationCode0
Conversational Disease Diagnosis via External Planner-Controlled Large Language ModelsCode0
Constraining the Parameters of High-Dimensional Models with Active LearningCode0
Constrained Multi-objective Bayesian Optimization through Optimistic Constraints EstimationCode0
Context Selection and Rewriting for Video-based Educational Question GenerationCode0
Cooperative Inverse Reinforcement LearningCode0
Confidence-Aware Active Feedback for Interactive Instance SearchCode0
Compute-Efficient Active LearningCode0
Conditional Normalizing Flows for Active Learning of Coarse-Grained Molecular RepresentationsCode0
Continual Active Learning Using Pseudo-Domains for Limited Labelling Resources and Changing Acquisition CharacteristicsCode0
Active Learning on Neural Networks through Interactive Generation of Digit Patterns and Visual RepresentationCode0
Continual egocentric object recognitionCode0
Active Learning of Spin Network ModelsCode0
Composite Active Learning: Towards Multi-Domain Active Learning with Theoretical GuaranteesCode0
Computational Assessment of Hyperpartisanship in News TitlesCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TypiClustAccuracy93.2—Unverified
2PT4ALAccuracy93.1—Unverified
3Learning lossAccuracy91.01—Unverified
4CoreGCNAccuracy90.7—Unverified
5Core-setAccuracy89.92—Unverified
6Random Baseline (Resnet18)Accuracy88.45—Unverified
7Random Baseline (VGG16)Accuracy85.09—Unverified