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 2626–2650 of 3073 papers

TitleStatusHype
Deep Bayesian Active Learning with Image DataCode0
Deep Bayesian Active Semi-Supervised LearningCode0
Characterizing the robustness of Bayesian adaptive experimental designs to active learning biasCode0
STENCIL: Submodular Mutual Information Based Weak Supervision for Cold-Start Active LearningCode0
Deep Diffusion Processes for Active Learning of Hyperspectral ImagesCode0
CFlowNets: Continuous Control with Generative Flow NetworksCode0
CAMAL: Optimizing LSM-trees via Active LearningCode0
Pool-Based Sequential Active Learning for RegressionCode0
Active Learning for Top-K Rank Aggregation from Noisy ComparisonsCode0
Deeper Connections between Neural Networks and Gaussian Processes Speed-up Active LearningCode0
Combining Data Generation and Active Learning for Low-Resource Question AnsweringCode0
Calpric: Inclusive and Fine-grain Labeling of Privacy Policies with Crowdsourcing and Active LearningCode0
Multi-Domain Active Learning: Literature Review and Comparative StudyCode0
Deeply Supervised Active Learning for Finger Bones SegmentationCode0
Is Policy Learning Overrated?: Width-Based Planning and Active Learning for AtariCode0
ACTIVETHIEF: Model Extraction Using Active Learning and Unannotated Public DataCode0
Improving OCR Accuracy on Early Printed Books by combining Pretraining, Voting, and Active LearningCode0
Stochastic Deep Networks with Linear Competing Units for Model-Agnostic Meta-LearningCode0
Active Learning via Membership Query Synthesis for Semi-Supervised Sentence ClassificationCode0
Improving Question Answering Performance Using Knowledge Distillation and Active LearningCode0
Active learning via informed search in movement parameter space for efficient robot task learning and transferCode0
Multi-Label Bayesian Active Learning with Inter-Label RelationshipsCode0
Accelerating materials discovery for polymer solar cells: Data-driven insights enabled by natural language processingCode0
Improving traffic sign recognition by active searchCode0
Variational Factorization Machines for Preference Elicitation in Large-Scale Recommender SystemsCode0
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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