| Learning from Noisy Labels with Deep Neural Networks: A Survey H Song, M Kim, D Park, Y Shin, JG Lee Transactions on Neural Networks and Learning Systems (TNNLS), 2022 | 959 | 2022 |
| SELFIE: Refurbishing Unclean Samples for Robust Deep Learning H Song, M Kim, JG Lee International Conference on Machine Learning (ICML), 2019 | 398 | 2019 |
| Data Collection and Quality Challenges in Deep Learning: A Data-Centric AI Perspective SE Whang, Y Roh, H Song, JG Lee International Journal on Very Large Data Bases (VLDBJ), 2023 | 194 | 2023 |
| Dataset Condensation via Efficient Synthetic-Data Parameterization JH Kim, J Kim, SJ Oh, S Yun, H Song, J Jeong, JW Ha, HO Song International Conference on Machine Learning (ICML), 2022 | 102 | 2022 |
| 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 | 102* | 2021 |
| ViDT: An Efficient and Effective Fully Transformer-based Object Detector H Song, D Sun, S Chun, V Jampani, D Han, B Heo, W Kim, MH Yang International Conference on Learning Representation (ICLR), 2022 | 92* | 2022 |
| RP-DBSCAN: A Superfast Parallel DBSCAN Algorithm based on Random Partitioning H Song, JG Lee International Conference on Management of Data (SIGMOD), 2018 | 68 | 2018 |
| PAMAE: Parallel k-Medoids Clustering with High Accuracy and Efficiency H Song, JG Lee, WS Han International Conference on Knowledge Discovery and Data Mining (KDD), 2017 | 52 | 2017 |
| Online Continual Learning on a Contaminated Data Stream with Blurry Task Boundaries J Bang, H Koh, S Park, H Song, JW Ha, J Choi International Conference on Computer Vision and Pattern Recognition (CVPR), 2022 | 41 | 2022 |
| 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 | 39* | 2020 |
| Understanding Cross-domain Few-shot Learning: An Experimental Study J Oh, S Kim, N Ho, JH Kim, H Song, SY Yun Annual Conference on Neural Information Processing Systems (NeurIPS), 2022 | 30* | 2022 |
| Fast and Robust Early-Exiting Framework for Autoregressive Language Models with Synchronized Parallel Decoding S Bae, J Ko, H Song, SY Yun Empirical Methods in Natural Language Processing (EMNLP), 2023 | 21 | 2023 |
| 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 | 16 | 2022 |
| Machine Learning Robustness, Fairness, and their Convergence JG Lee, Y Roh, H Song, SE Whang International Conference on Knowledge Discovery and Data Mining (KDD), 2021 | 16 | 2021 |
| Ada-Boundary: Accelerating DNN Training via Adaptive Boundary Batch Selection H Song, S Kim, M Kim, JG Lee Machine Learning (ML), 2020 | 16 | 2020 |
| Carpe Diem, Seize the Samples Uncertain "At the Moment" for Adaptive Batch Selection H Song, M Kim, S Kim, JG Lee International Conference on Information and Knowledge Management (CIKM), 2020 | 15 | 2020 |
| PREMERE: Meta-Reweighting via Self-Ensembling for Point-of-Interest Recommendation M Kim, H Song, D Kim, S Kijung, JG Lee AAAI Conference on Artificial Intelligence (AAAI), 2021 | 14 | 2021 |
| Online Boundary-Free Continual Learning by Scheduled Data Prior H Koh, M Seo, J Bang, H Song, D Hong, S Park, JW Ha, J Choi International Conference on Learning Representation (ICLR), 2023 | 13 | 2023 |
| 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 | 12 | 2022 |
| Generating Instance-level Prompts for Rehearsal-free Continual Learning D Jung, D Han, J Bang, H Song International Conference on Computer Vision (ICCV), 2023 | 11 | 2023 |
Jae-Gil LeeProfessor, School of Computing, KAIST在 kaist.ac.kr 的电子邮件经过验证
