| Learning from noisy labels with deep neural networks: A survey H Song, M Kim, D Park, Y Shin, JG Lee IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022 | 1282 | 2022 |
| Prestopping: How does early stopping help generalization against label noise? H Song, M Kim, D Park, JG Lee ICML Workshop, 2019 | 86* | 2019 |
| Robust Learning by Self-Transition for Handling Noisy Labels H Song, M Kim, D Park, Y Shin, JG Lee International Conference on Knowledge Discovery and Data Mining (KDD), 2021 | 47 | 2021 |
| Hi-COVIDNet: Deep Learning Approach to Predict Inbound COVID-19 Patients and Case Study in South Korea M Kim, J Kang, D Kim, H Song, H Min, Y Nam, D Park, JG Lee International Conference on Knowledge Discovery and Data Mining (KDD), 2020 | 40 | 2020 |
| Robust Data Pruning under Label Noise via Maximizing Re-labeling Accuracy D Park, S Choi, D Kim, H Song, JG Lee Annual Conference on Neural Information Processing Systems (NeurIPS), 2023 | 22 | 2023 |
| Active Learning is a Strong Baseline for Data Subset Selection D Park, D Papailiopoulos, K Lee NeurIPS Workshop, 2022 | 21 | 2022 |
| Meta-Query-Net: Resolving Purity-Informativeness Dilemma in Open-set Active Learning D Park, Y Shin, J Bang, Y Lee, H Song, JG Lee Annual Conference on Neural Information Processing Systems (NeurIPS), 2022 | 20 | 2022 |
| Meta-Learning for Online Update of Recommender Systems M Kim, H Song, Y Shin, D Park, K Shin, JG Lee AAAI Conference on Artificial Intelligence (AAAI), 2022 | 19 | 2022 |
| Mitigating Dialogue Hallucination for Large Multi-modal Models via Adversarial Instruction Tuning D Park, Z Qian, G Han, SN Lim arXiv preprint arXiv:2403.10492, 2024 | 13 | 2024 |
| TRAP: Two-level Regularized Autoencoder-based Embedding for Power-law Distributed Data D Park, H Song, M Kim, JG Lee The Web Conference (WWW), oral, 2020 | 11 | 2020 |
| Task-Agnostic Undesirable Feature Deactivation Using Out-of-Distribution Data D Park, H Song, MS Kim, JG Lee Annual Conference on Neural Information Processing Systems (NeurIPS), 2021 | 10 | 2021 |
| Context Consistency Regularization for Label Sparsity in Time Series Y Shin, S Yoon, H Song, D Park, B Kim, JG Lee, BS Lee International Conference on Machine Learning (ICML), 2023 | 8 | 2023 |
| One Size Fits All for Semantic Shifts: Adaptive Prompt Tuning for Continual Learning D Kim, S Yoon, D Park, Y Lee, H Song, J Bang, JG Lee International Conference on Machine Learning (ICML), 2024 | 3 | 2024 |
| Multi-view POI-level Cellular Trajectory Reconstruction for Digital Contact Tracing of Infectious Diseases D Park, J Kang, H Song, S Yoon, JG Lee International Conference on Data Mining (ICDM), 2022 | 3 | 2022 |
| Adaptive Shortcut Debiasing for Online Continual Learning D Kim, D Park, Y Shin, J Bang, H Song, JG Lee AAAI Conference on Artificial Intelligence (AAAI), 2024 | 2 | 2024 |
| Test-time Alignment of Diffusion Models without Reward Over-optimization S Kim, M Kim, D Park International Conference on Learning Representation (ICLR), spotlight, 2025 | 1* | 2025 |
| Rare-to-Frequent: Unlocking Compositional Generation Power of Diffusion Models on Rare Concepts with LLM Guidance D Park, S Kim, T Moon, M Kim, K Lee, J Cho International Conference on Learning Representation (ICLR), spotlight, 2025 | 1 | 2025 |
| MLAT: Metric Learning for kNN in Streaming Time Series D Park, S Yoon, H Song, JG Lee KDD Workshop, 2019 | 1 | 2019 |
| Active Learning for Continual Learning: Keeping the Past Alive in the Present J Park, D Park, JG Lee International Conference on Learning Representation (ICLR), 2025 | | 2025 |
| Prioritizing Informative Features and Examples for Deep Learning from Noisy Data D Park Ph.D. Dissertation, 2024 | | 2024 |
Hwanjun SongAssistant Professor, KAISTVerifisert e-postadresse på kaist.ac.kr