active learning

Phrase-level Active Learning for Neural Machine Translation EMNLP 2021 Planning Multimodal Exploratory Actions for Online Robot Attribute Learning RSS 2021 QActor: Active Learning on Noisy Labels ACML 2021 ReDAL: Region-Based and Diversity-Aware Active Learning for Point Cloud Semantic Segmentation ICCV 2021 Reliable Estimates of Interpretable Cue Effects with Active Learning in Psycholinguistic Research Interspeech 2021 Revisiting Model-Agnostic Private Learning: Faster Rates and Active Learning AISTATS 2021 Revisiting Model-Agnostic Private Learning: Faster Rates and Active Learning JMLR 2021 Revisiting Superpixels for Active Learning in Semantic Segmentation With Realistic Annotation Costs CVPR 2021 RIM: Reliable Influence-based Active Learning on Graphs NeurIPS 2021 SEAL: Self-supervised Embodied Active Learning using Exploration and 3D Consistency NeurIPS 2021 Semi-Supervised Active Learning for Semi-Supervised Models: Exploit Adversarial Examples With Graph-Based Virtual Labels ICCV 2021 Semi-Supervised Active Learning With Temporal Output Discrepancy ICCV 2021 Semi-Supervised Learning via Triplet Network Based Active Learning (Student Abstract) AAAI 2021 Sequential Graph Convolutional Network for Active Learning CVPR 2021 SIMILAR: Submodular Information Measures Based Active Learning In Realistic Scenarios NeurIPS 2021 SPADE: A Semi-supervised Probabilistic Approach for Detecting Errors in Tables IJCAI 2021 Subsequence Based Deep Active Learning for Named Entity Recognition ACL 2021 Supporting Land Reuse of Former Open Pit Mining Sites using Text Classification and Active Learning ACL 2021 TAILOR: Teaching with Active and Incremental Learning for Object Registration AAAI 2021 Task-Aware Variational Adversarial Active Learning CVPR 2021 Teaching Active Human Learners AAAI 2021 Teaching an Active Learner with Contrastive Examples NeurIPS 2021 Teaching via Best-Case Counterexamples in the Learning-with-Equivalence-Queries Paradigm NeurIPS 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 Toward a General Theory of Online Selective Sampling: Trading Off Mistakes and Queries AISTATS 2021