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 1151–1200 of 3073 papers

TitleStatusHype
Decision Trees for Function Evaluation - Simultaneous Optimization of Worst and Expected Cost—0
Constrained Online Decision-Making: A Unified Framework—0
Coresets for Classification -- Simplified and Strengthened—0
Coresets for Classification – Simplified and Strengthened—0
Adaptive Local Kernels Formulation of Mutual Information with Application to Active Post-Seismic Building Damage Inference—0
Active and sparse methods in smoothed model checking—0
Corruption Robust Active Learning—0
Adding more data does not always help: A study in medical conversation summarization with PEGASUS—0
Constrained Bayesian Optimization with Adaptive Active Learning of Unknown Constraints—0
Cost-Based Budget Active Learning for Deep Learning—0
Addressing Limited Data for Textual Entailment Across Domains—0
Active Learning for Point Cloud Semantic Segmentation via Spatial-Structural Diversity Reasoning—0
Addressing practical challenges in Active Learning via a hybrid query strategy—0
Active Learning for Post-Editing Based Incrementally Retrained MT—0
Cost-Effective Proxy Reward Model Construction with On-Policy and Active Learning—0
Cost-Effective Training in Low-Resource Neural Machine Translation—0
Constrained Bayesian Active Learning of Interference Channels in Cognitive Radio Networks—0
Cost-effective Variational Active Entity Resolution—0
Importance sampling based active learning for parametric seismic fragility curve estimation—0
Cost-Quality Adaptive Active Learning for Chinese Clinical Named Entity Recognition—0
Cost-Sensitive Active Learning for Intracranial Hemorrhage Detection—0
Cost-Sensitive Active Learning for Dialogue State Tracking—0
A Deep Learning Driven Active Framework for Segmentation of Large 3D Shape Collections—0
Active Learning for Product Type Ontology Enhancement in E-commerce—0
CoTAL: Human-in-the-Loop Prompt Engineering, Chain-of-Thought Reasoning, and Active Learning for Generalizable Formative Assessment Scoring—0
Counterfactual Contextual Multi-Armed Bandit: a Real-World Application to Diagnose Apple Diseases—0
DECAL: DEployable Clinical Active Learning—0
A domain-decomposed VAE method for Bayesian inverse problems—0
CPRAL: Collaborative Panoptic-Regional Active Learning for Semantic Segmentation—0
CRAB Reader: A Tool for Analysis and Visualization of Argumentative Zones in Scientific Literature—0
Consistent Training via Energy-Based GFlowNets for Modeling Discrete Joint Distributions—0
Consistency-Based Semi-supervised Evidential Active Learning for Diagnostic Radiograph Classification—0
Active Learning for Non-Parametric Choice Models—0
Consistency-based Semi-supervised Active Learning: Towards Minimizing Labeling Cost—0
Critic Loss for Image Classification—0
CRL+: A Novel Semi-Supervised Deep Active Contrastive Representation Learning-Based Text Classification Model for Insurance Data—0
Advances in Hyperspectral Image Classification: Earth monitoring with statistical learning methods—0
Active learning for regression in engineering populations: A risk-informed approach—0
Cross-lingual German Biomedical Information Extraction: from Zero-shot to Human-in-the-Loop—0
Cross-Model Image Annotation Platform with Active Learning—0
Consistency-Based Semi-Supervised Active Learning: Towards Minimizing Labeling Budget—0
Cross-Task Inconsistency Based Active Learning (CTIAL) for Emotion Recognition—0
Adversarial Active Learning based Heterogeneous Graph Neural Network for Fake News Detection—0
Binary Classification with XOR Queries: Fundamental Limits and An Efficient Algorithm—0
Crowd Sourcing based Active Learning Approach for Parking Sign Recognition—0
Crowdsourcing Complex Language Resources: Playing to Annotate Dependency Syntax—0
Adaptive Defective Area Identification in Material Surface Using Active Transfer Learning-based Level Set Estimation—0
Crown-Like Structures in Breast Adipose Tissue: Finding a 'Needle-in-a-Haystack' using Artificial Intelligence and Collaborative Active Learning on the Web—0
Accelerating engineering design by automatic selection of simulation cases through Pool-Based Active Learning—0
Deciding when to stop: Efficient stopping of active learning guided drug-target prediction—0
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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