Search Results - Jae, Hwanjun

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  1. 1
    Percutaneous Mechanical Thrombectomy of Submassive Pulmonary Embolism and Extensive Deep Venous Thrombosis for Early Thrombus Removal

    Percutaneous Mechanical Thrombectomy of Submassive Pulmonary Embolism and Extensive Deep Venous Thrombosis for Early Thrombus Removal by Jo, Eun-Ah, Choi, Kwang Woo, Han, Ahram, Ahn, Sanghyun, Min, Sangil, Jae, Hwanjun, Lee, Myungsu, Min, Seung-Kee

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  2. 2
    One-year outcomes of the U.S. and Japanese regulatory trial of the Misago stent for treatment of superficial femoral artery disease (OSPREY study)

    One-year outcomes of the U.S. and Japanese regulatory trial of the Misago stent for treatment of superficial femoral artery disease (OSPREY study) by Ohki, Takao, MD, Angle, John F., MD, Yokoi, Hiroyoshi, MD, Jaff, Michael R., DO, Popma, Jeffrey, MD, Piegari, Guy, MD, Kanaoka, Yuji, MD

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  3. 3
    Efficacy and safety of the computed tomography coronary angiography based approach for patients with acute chest pain at an emergency department: one month clinical follow-up study

    Efficacy and safety of the computed tomography coronary angiography based approach for patients with acute chest pain at an emergency department: one month clinical follow-up study by Kim, Joonghee, Lee, Hwijae, Song, Sungwook, Park, Jinsik, Jae, Hwanjun, Lee, Whal, Shin, Sangdo, Jung, Sungkoo, Kwak, Youngho, Suh, Giljoon, Park, Jaehyung

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  4. 4
    Data collection and quality challenges in deep learning: a data-centric AI perspective

    Data collection and quality challenges in deep learning: a data-centric AI perspective by Whang, Steven Euijong, Roh, Yuji, Song, Hwanjun, Lee, Jae-Gil

    Published in The VLDB journal
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  5. 5
    Learning From Noisy Labels With Deep Neural Networks: A Survey

    Learning From Noisy Labels With Deep Neural Networks: A Survey by Song, Hwanjun, Kim, Minseok, Park, Dongmin, Shin, Yooju, Lee, Jae-Gil

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  6. 6
    Ada-boundary: accelerating DNN training via adaptive boundary batch selection

    Ada-boundary: accelerating DNN training via adaptive boundary batch selection by Song, Hwanjun, Kim, Sundong, Kim, Minseok, Lee, Jae-Gil

    Published in Machine learning
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  7. 7
    Toward Robustness in Multi-Label Classification: A Data Augmentation Strategy against Imbalance and Noise

    Toward Robustness in Multi-Label Classification: A Data Augmentation Strategy against Imbalance and Noise by Song, Hwanjun, Kim, Minseok, Lee, Jae-Gil

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  8. 8
    Adaptive Shortcut Debiasing for Online Continual Learning

    Adaptive Shortcut Debiasing for Online Continual Learning by Kim, Doyoung, Park, Dongmin, Shin, Yooju, Bang, Jihwan, Song, Hwanjun, Lee, Jae-Gil

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  9. 9
    Multi-view POI-level Cellular Trajectory Reconstruction for Digital Contact Tracing of Infectious Diseases

    Multi-view POI-level Cellular Trajectory Reconstruction for Digital Contact Tracing of Infectious Diseases by Park, Dongmin, Kang, Junhyeok, Song, Hwanjun, Yoon, Susik, Lee, Jae-Gil

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  10. 10
    Toward Robustness in Multi-label Classification: A Data Augmentation Strategy against Imbalance and Noise

    Toward Robustness in Multi-label Classification: A Data Augmentation Strategy against Imbalance and Noise by Song, Hwanjun, Kim, Minseok, Jae-Gil, Lee

    Published in arXiv.org
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  11. 11
    Meta-Learning for Online Update of Recommender Systems

    Meta-Learning for Online Update of Recommender Systems by Kim, Minseok, Song, Hwanjun, Shin, Yooju, Park, Dongmin, Shin, Kijung, Lee, Jae-Gil

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  12. 12
    PREMERE: Meta-Reweighting via Self-Ensembling for Point-of-Interest Recommendation

    PREMERE: Meta-Reweighting via Self-Ensembling for Point-of-Interest Recommendation by Kim, Minseok, Song, Hwanjun, Kim, Doyoung, Shin, Kijung, Lee, Jae-Gil

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  13. 13
    COVID-EENet: Predicting Fine-Grained Impact of COVID-19 on Local Economies

    COVID-EENet: Predicting Fine-Grained Impact of COVID-19 on Local Economies by Kim, Doyoung, Min, Hyangsuk, Nam, Youngeun, Song, Hwanjun, Yoon, Susik, Kim, Minseok, Lee, Jae-Gil

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  14. 14
    Robust Learning by Self-Transition for Handling Noisy Labels

    Robust Learning by Self-Transition for Handling Noisy Labels by Song, Hwanjun, Kim, Minseok, Park, Dongmin, Shin, Yooju, Jae-Gil, Lee

    Published in arXiv.org
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  15. 15
    Data Collection and Quality Challenges in Deep Learning: A Data-Centric AI Perspective

    Data Collection and Quality Challenges in Deep Learning: A Data-Centric AI Perspective by Whang, Steven Euijong, Roh, Yuji, Song, Hwanjun, Jae-Gil, Lee

    Published in arXiv.org
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  16. 16
    One Size Fits All for Semantic Shifts: Adaptive Prompt Tuning for Continual Learning

    One Size Fits All for Semantic Shifts: Adaptive Prompt Tuning for Continual Learning by Kim, Doyoung, Yoon, Susik, Park, Dongmin, Lee, Youngjun, Song, Hwanjun, Bang, Jihwan, Jae-Gil, Lee

    Published in arXiv.org
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  17. 17
    Adaptive Shortcut Debiasing for Online Continual Learning

    Adaptive Shortcut Debiasing for Online Continual Learning by Kim, Doyoung, Park, Dongmin, Shin, Yooju, Bang, Jihwan, Song, Hwanjun, Jae-Gil, Lee

    Published in arXiv.org
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  18. 18
    Robust Data Pruning under Label Noise via Maximizing Re-labeling Accuracy

    Robust Data Pruning under Label Noise via Maximizing Re-labeling Accuracy by Park, Dongmin, Choi, Seola, Kim, Doyoung, Song, Hwanjun, Jae-Gil, Lee

    Published in arXiv.org
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  19. 19
    Meta-Query-Net: Resolving Purity-Informativeness Dilemma in Open-set Active Learning

    Meta-Query-Net: Resolving Purity-Informativeness Dilemma in Open-set Active Learning by Park, Dongmin, Shin, Yooju, Bang, Jihwan, Lee, Youngjun, Song, Hwanjun, Jae-Gil, Lee

    Published in arXiv.org
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  20. 20
    How does Early Stopping Help Generalization against Label Noise?

    How does Early Stopping Help Generalization against Label Noise? by Song, Hwanjun, Kim, Minseok, Park, Dongmin, Jae-Gil, Lee

    Published in arXiv.org
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