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Dongmin Park
Email: dongminparkxkxkxk@kaist.ac.kr Phone: +82 o1o-8q37-8424 |
Dec 2023: Passed my Ph.D. Defense :)
Dec 2023: A Paper on 'Adaptive Shorcut Debiasing for Online Continual Learning' Accepted to AAAI 2024.
Dec 2023: A Paper on 'Data Pruning under Label Noise' published at NeurIPS 2023.
Jul 2023: A Paper on 'Time-series Semi-supervised Learning' published at ICML 2023.
Jun 2023: Started 'AI Research Internship' at Meta AI.
May 2023: Passed my Ph.D. Proposal. Work Experience
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D. Kim, D. Park, Y. Shin, J. Bang, H. Song, JG. Lee. Adaptive Shorcut Debiasing for Online Continual Learning. The AAAI Conference on Artificial Intelligence (AAAI) 2024. |
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D. Park, S. Choi, D. Kim, H. Song, JG. Lee. Robust Data Pruning under Label Noise via Maximizing Re-labeling Accuracy. Annual Conference on Neural Information Processing Systems (NeurIPS) 2023. [pdf] [code] |
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Y. Shin, S. Yoon, H. Song, D. Park, B. Kim, JG. Lee, BS. Lee. Context Consistency Regularization for Label Sparsity in Time Series. International Conference on Machine Learning (ICML) 2023. [pdf] |
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D. Park, Y. Shin, J. Bang, Y. Lee, H. Song, JG. Lee. Meta-Query-Net: Resolving Purity-Informativeness Dilemma in Open-set Active Learning. Annual Conference on Neural Information Processing Systems (NeurIPS) 2022. [pdf] [code] |
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D. Park, D. Papailiopoulos, K. Lee. Active Learning is a Strong Baseline for Data Subset Selection. Has it Trained Yet? Workshop on Annual Conference on Neural Information Processing Systems (NeurIPS, Workshop) 2022. [pdf] [code] |
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D. Park, J. Kang, H. Song, S. Yoon, JG Lee. Multi-view POI-level Cellular Trajectory Reconstruction for Digital Contact Tracing of Infectious Diseases. International Conference on Data Minig (ICDM) 2022. [pdf] |
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H. Song, M. Kim, D. Park, Y. Shin, JG. Lee. Learning from Noisy Labels with Deep Neural Networks: A Survey. IEEE Transactions on Neural Networks and Learning Systems (TNNLS) 2022. The most cited survey paper on handling noisy labels with DNNs. [pdf] [code] |
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M. Kim, H. Song, Y. Shin, D. Park, K. Shin, JG. Lee. Meta-Learning for Online Update of Recommender Systems. The AAAI Conference on Artificial Intelligence (AAAI) 2022. [pdf] |
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D. Park, H. Song, M. Kim, JG. Lee. Task-Agnostic Undesirable Feature Deactivation Using Out-of-Distribution Data. Annual Conference on Neural Information Processing Systems (NeurIPS) 2021. [pdf] [code] |
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H. Song, M. Kim, D. Park, Y. Shin, JG. Lee. Robust Learning by Self-Transition for Handling Noisy Labels. International Conference on Knowledge Discovery and Data Mining (KDD) 2021. Oral Presentation. [pdf] |
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M. Kim, J. Kang, Dim, H. Song, H. Min, Y. Nam, D. Park, JG. Lee. Hi-COVIDNet: Deep Learning Approach to Predict Inbound COVID-19 Patients and Case Study in South Korea . International Conference on Knowledge Discovery and Data Mining (KDD) 2020. Oral Presentation. [pdf] [code] |
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H. Song, M. Kim, D. Park, JG. Lee. How Does Early Stopping Help Generalization against Label Noise? . International Conference on Machine Learning (ICML, Workshop) 2020. [pdf] [code] |
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D. Park, H. Song, M. Kim, JG. Lee. TRAP: Two-level Regularized Autoencoder-based Embedding for Power-law Distributed Data. TheWebConf (WWW) 2020. Oral Presentation. [pdf] [code] |
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D. Park, S. Yoon, H. Song, JG. Lee. MLAT: Metric Learning for kNN in Streaming Time Series. International Conference on Knowledge Discovery and Data Mining (KDD, Workshop) 2019. [pdf] |
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Reviewer for ICML, NeurIPS, ICLR, CVPR, ICCV, KDD, AAAI, TNNLS since 2021
Awards© 2022 Dongmin Park. Thanks Dr. Hwanjun Song and Dr. Deqing Sun for the template.