Resultado de búsqueda
Jun Shu currently works at the School of Mathematics and Statistics, Xi'an Jiaotong University. Jun does research in Statistics and Applied Mathematics. Their most recent publication is...
SHU Jun, M Deyu, XU Zongben. Scientia Sinica Informationis 50 (6), 781-793, 2020. 15 * 2020: Learning an explicit hyperparameter prediction function conditioned on tasks. J Shu, D Meng, Z Xu. Journal of Machine Learning Research, 2023. 11 * 2023: MLR-SNet: Transferable LR Schedules for Heterogeneous Tasks.
11 de feb. de 2022 · CMW-Net: Learning a Class-Aware Sample Weighting Mapping for Robust Deep Learning. Jun Shu, Xiang Yuan, Deyu Meng, Zongben Xu. Modern deep neural networks can easily overfit to biased training data containing corrupted labels or class imbalance.
6 de jul. de 2021 · Learning an Explicit Hyperparameter Prediction Function Conditioned on Tasks. Jun Shu, Deyu Meng, Zongben Xu. Meta learning has attracted much attention recently in machine learning community. Contrary to conventional machine learning aiming to learn inherent prediction rules to predict labels for new query data, meta learning aims ...
Biography. Jun Shu received the BE degree from Xi’an Jiaotong University, Xi’an, China, in 2016, where he is currently working toward the PhD degree, under the tuition of Prof. Deyu Meng and Prof. Zongben Xu. His current research interests include machine learning and computer vision, especially on meta learning, robust deep learning, and ...
Synthetic and real experiments substantiate the capability of our method for achieving proper weighting functions in class imbalance and noisy label cases, fully complying with the common settings in traditional methods, and more complicated scenarios beyond conventional cases.
Jun Shu. MLR-SNet: Transferable LR Schedules for Heterogeneous Tasks. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2022 | Journal article. DOI: 10.1109/tpami.2022.3184315. Part of ISSN: 0162-8828. Part of ISSN: 2160-9292. Part of ISSN: 1939-3539. Contributors : Jun Shu.
