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

Showing 251300 of 3073 papers

TitleStatusHype
Efficiently Learning at Test-Time: Active Fine-Tuning of LLMsCode2
A Utility-Mining-Driven Active Learning Approach for Analyzing Clickstream Sequences0
MelissaDL x Breed: Towards Data-Efficient On-line Supervised Training of Multi-parametric Surrogates with Active Learning0
Interactive Event Sifting using Bayesian Graph Neural Networks0
Improved detection of discarded fish species through BoxAL active learningCode0
Language Model-Driven Data Pruning Enables Efficient Active Learning0
STONE: A Submodular Optimization Framework for Active 3D Object DetectionCode0
Active Learning of Deep Neural Networks via Gradient-Free Cutting Planes0
Structural-Entropy-Based Sample Selection for Efficient and Effective Learning0
Dual Active Learning for Reinforcement Learning from Human Feedback0
GPT-4o as the Gold Standard: A Scalable and General Purpose Approach to Filter Language Model Pretraining Data0
Provably Accurate Shapley Value Estimation via Leverage Score Sampling0
Differentially Private Active Learning: Balancing Effective Data Selection and PrivacyCode0
Efficient Quality Control of Whole Slide Pathology Images with Human-in-the-loop TrainingCode0
Sustaining model performance for covid-19 detection from dynamic audio data: Development and evaluation of a comprehensive drift-adaptive framework0
AL-GTD: Deep Active Learning for Gaze Target DetectionCode1
Towards an active-learning approach to resource allocation for population-based damage prognosis0
A3: Active Adversarial Alignment for Source-Free Domain AdaptationCode0
Find Rhinos without Finding Rhinos: Active Learning with Multimodal Imagery of South African Rhino HabitatsCode0
Dirichlet-Based Coarse-to-Fine Example Selection For Open-Set Annotation0
Reactive Multi-Robot Navigation in Outdoor Environments Through Uncertainty-Aware Active Learning of Human Preference Landscape0
Open-/Closed-loop Active Learning for Data-driven Predictive Control0
From Passive Watching to Active Learning: Empowering Proactive Participation in Digital Classrooms with AI Video Assistant0
Critic Loss for Image Classification0
CAMAL: Optimizing LSM-trees via Active LearningCode0
The trade-off between data minimization and fairness in collaborative filtering0
SANE: Strategic Autonomous Non-Smooth Exploration for Multiple Optima Discovery in Multi-modal and Non-differentiable Black-box Functions0
Accelerating the Training and Improving the Reliability of Machine-Learned Interatomic Potentials for Strongly Anharmonic Materials through Active Learning0
Enhancing Semi-Supervised Learning via Representative and Diverse Sample SelectionCode0
Active learning for energy-based antibody optimization and enhanced screening0
Diversify and Conquer: Diversity-Centric Data Selection with Iterative RefinementCode1
Active Learning to Guide Labeling Efforts for Question Difficulty EstimationCode0
MALADY: Multiclass Active Learning with Auction Dynamics on Graphs0
Crown-Like Structures in Breast Adipose Tissue: Finding a 'Needle-in-a-Haystack' using Artificial Intelligence and Collaborative Active Learning on the Web0
DEMAU: Decompose, Explore, Model and Analyse Uncertainties0
A Scalable Algorithm for Active Learning0
STAND: Data-Efficient and Self-Aware Precondition Induction for Interactive Task Learning0
Automated Discovery of Pairwise Interactions from Unstructured Data0
FIRAL: An Active Learning Algorithm for Multinomial Logistic Regression0
Bounds on the Generalization Error in Active Learning0
A Bayesian Framework for Active Tactile Object Recognition, Pose Estimation and Shape Transfer Learning0
Applied Federated Model Personalisation in the Industrial Domain: A Comparative Study0
Distribution Discrepancy and Feature Heterogeneity for Active 3D Object DetectionCode0
Interactive Machine Teaching by Labeling Rules and Instances0
Deep Bayesian Active Learning-to-Rank with Relative Annotation for Estimation of Ulcerative Colitis Severity0
Active learning for regression in engineering populations: A risk-informed approach0
MOBIUS: Towards the Next Generation of Query-Ad Matching in Baidu's Sponsored Search0
An incremental preference elicitation-based approach to learning potentially non-monotonic preferences in multi-criteria sorting0
Active Symbolic Discovery of Ordinary Differential Equations via Phase Portrait SketchingCode0
Adaptive Open-Set Active Learning with Distance-Based Out-of-Distribution Detection for Robust Task-Oriented Dialog SystemCode0
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Benchmark Results

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