← Learning Types
Machine Learning › Learning Types ›

Active Learning

1885 directly classified papers

Papers per year

Papers

Towards robust episodic meta-learning UAI 2021
Active multi-fidelity Bayesian online changepoint detection UAI 2021
Possibilistic preference elicitation by minimax regret UAI 2021
CLAIM: curriculum learning policy for influence maximization in unknown social networks UAI 2021
Simple and Fast Algorithms for Interactive Machine Learning with Random Counter-examples JMLR 2021
Interaction Considerations in Learning from Humans IJCAI 2021
Exponential savings in agnostic active learning through abstention COLT 2021
Exponential Weights Algorithms for Selective Learning COLT 2021
Efficient Bandit Convex Optimization: Beyond Linear Losses COLT 2021
Active Learning for Rumor Identification on Social Media EMNLP 2021
ActiveEA: Active Learning for Neural Entity Alignment EMNLP 2021
Active Learning by Acquiring Contrastive Examples EMNLP 2021
QActor: Active Learning on Noisy Labels ACML 2021
A Clustering-based framework for Classifying Data Streams IJCAI 2021
The University of Arizona at SemEval-2021 Task 10: Applying Self-training, Active Learning and Data Augmentation to Source-free Domain Adaptation SEMEVAL 2021
Paladin: an annotation tool based on active and proactive learning EACL 2021
Selecting Informative Contexts Improves Language Model Fine-tuning IJCNLP 2021
Human-in-the-Loop for Data Collection: a Multi-Target Counter Narrative Dataset to Fight Online Hate Speech IJCNLP 2021
Supporting Land Reuse of Former Open Pit Mining Sites using Text Classification and Active Learning IJCNLP 2021
Self-Guided Curriculum Learning for Neural Machine Translation IJCNLP 2021
Tackling Fake News Detection by Interactively Learning Representations using Graph Neural Networks IJCNLP 2021
ArgFuse: A Weakly-Supervised Framework for Document-Level Event Argument Aggregation IJCNLP 2021
Active Curriculum Learning IJCNLP 2021
Generic Oracles for Structured Prediction IJCNLP 2021
The University of Arizona at SemEval-2021 Task 10: Applying Self-training, Active Learning and Data Augmentation to Source-free Domain Adaptation ACL 2021