- Asynchronous Active Learning with Distributed Label Querying [2021, IJCAI]
- Dual Active Learning for Both Model and Data Selection [2021, IJCAI]
- A Comparative Survey: Benchmarking for Pool-based Active Learning [2021, IJCAI]
- Class Prior Estimation in Active Positive and Unlabeled Learning [2020, IJCAI]
- Batch Decorrelation for Active Metric Learning [2020, IJCAI]
- Deep Active Learning for Anchor User Prediction [IJCAI, 2019]
- Deeper Connections between Neural Networks and Gaussian Processes Speed-up Active Learning [IJCAI, 2019]
- Deeper Connections between Neural Networks and Gaussian Processes Speed-up Active Learning [2019, IJCAI]
- Adaptive Ensemble Active Learning for Drifting Data Stream Mining [2019, IJCAI]:
- Rapid Performance Gain through Active Model Reuse [IJCAI, 2019]
- Active discriminative network representation learning [2018, IJCAI]
- Cost-Effective Active Learning for Hierarchical Multi-Label Classification [2018, IJCAI]:
- Adversarial Active Learning for Sequence Labeling and Generation [2018, IJCAI]
- On Gleaning Knowledge from Multiple Domains for Active Learning [2017, IJCAI]
- Learning by Actively Querying Strong Modal Features [2016, IJCAI]
- Transfer Learning with Active Queries from Source Domain [2016, IJCAI]
- Semi-Supervised Active Learning with Cross-Class Sample Transfer [2016, IJCAI]
- Multi-Label Active Learning: Query Type Matters [2015, IJCAI]
- Active Learning from Crowds with Unsure Option [2015, IJCAI]
- Active learning with multi-label svm classification [2013, IJCAI]
- Active learning for cross-domain sentiment classification [2013, IJCAI]