Importance Weighted Active Learning
Papers citing "Importance Weighted Active Learning"
50 / 128 papers shown
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 Neural Active Learning Meets the Partial Monitoring FrameworkConference on Uncertainty in Artificial Intelligence (UAI), 2024 |
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 Inconsistency-Based Data-Centric Active Open-Set AnnotationAAAI Conference on Artificial Intelligence (AAAI), 2024 |
 Fair Active Learning in Low-Data RegimesConference on Uncertainty in Artificial Intelligence (UAI), 2023 |
 A Competitive Algorithm for Agnostic Active LearningNeural Information Processing Systems (NeurIPS), 2023 |
 Online Decision MediationNeural Information Processing Systems (NeurIPS), 2023 |
 Ensemble Active Learning by Contextual Bandits for AI Incubation in
ManufacturingACM Transactions on Intelligent Systems and Technology (ACM TIST), 2023 |
 Agnostic Multi-Group Active LearningNeural Information Processing Systems (NeurIPS), 2023 |
 Topic-Guided Sampling For Data-Efficient Multi-Domain Stance DetectionAnnual Meeting of the Association for Computational Linguistics (ACL), 2023 |
 Streaming Active Learning with Deep Neural NetworksInternational Conference on Machine Learning (ICML), 2023 |
 Active Learning with Combinatorial CoverageInternational Conference on Machine Learning and Applications (ICMLA), 2022 |
 Adaptive Selective Sampling for Online Prediction with ExpertsNeural Information Processing Systems (NeurIPS), 2023 |
 Leveraging Importance Weights in Subset SelectionInternational Conference on Learning Representations (ICLR), 2023 |
 Promises and Pitfalls of Threshold-based Auto-labelingNeural Information Processing Systems (NeurIPS), 2022 |
 A Two-Stage Active Learning Algorithm for -Nearest NeighborsInternational Conference on Machine Learning (ICML), 2022 |
 Active Learning with Neural Networks: Insights from Nonparametric
StatisticsNeural Information Processing Systems (NeurIPS), 2022 |
 Improved Algorithms for Neural Active LearningNeural Information Processing Systems (NeurIPS), 2022 |
 Active learning algorithm through the lens of rejection argumentsMachine-mediated learning (ML), 2022 |
 Data-Efficient Learning via Minimizing Hyperspherical EnergyIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022 |
 Theory-Grounded Measurement of U.S. Social Stereotypes in English
Language ModelsNorth American Chapter of the Association for Computational Linguistics (NAACL), 2022 |
 Improving the quality control of seismic data through active learningSocial Science Research Network (SSRN), 2022 |
 Practical Active Learning with Model Selection for Small DataInternational Conference on Machine Learning and Applications (ICMLA), 2021 |
 Class-Balanced Active Learning for Image ClassificationIEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2021 |
 Corruption Robust Active LearningNeural Information Processing Systems (NeurIPS), 2021 |
 Neural Active Learning with Performance GuaranteesNeural Information Processing Systems (NeurIPS), 2021 |
 Improved Algorithms for Agnostic Pool-based Active ClassificationInternational Conference on Machine Learning (ICML), 2021 |
 Distribution Matching for Machine TeachingIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021 Xiaofeng Cao Ivor W. Tsang |
 Off-Policy Risk Assessment in Contextual BanditsNeural Information Processing Systems (NeurIPS), 2021 |
 Active Testing: Sample-Efficient Model EvaluationInternational Conference on Machine Learning (ICML), 2021 |
 Discrepancy-Based Active Learning for Domain AdaptationInternational Conference on Learning Representations (ICLR), 2021 |
 Feedback Coding for Active LearningInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2021 |
 Exponential Savings in Agnostic Active Learning through AbstentionIEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2021 |
 On Statistical Bias In Active Learning: How and When To Fix ItInternational Conference on Learning Representations (ICLR), 2021 |
 Learning in the Wild with Incremental Skeptical Gaussian ProcessesInternational Joint Conference on Artificial Intelligence (IJCAI), 2020 Andrea Bontempelli Stefano Teso Fausto Giunchiglia Andrea Passerini |
