Number of items: 13.
2023
Li, X., Yang, X. , Ma, Z. and Xue, J.-H.
(2023)
Deep metric learning for few-shot image classification: a review of recent developments.
Pattern Recognition, 138,
109381.
(doi: 10.1016/j.patcog.2023.109381)
Chen, Y. et al.
(2023)
Over-parameterized Model Optimization with Polyak-Łojasiewicz Condition.
In: 11th International Conference on Learning Representations (ICLR 2023), Kigali, Rwanda, 1-5 May 2023,
(Accepted for Publication)
2022
Li, Z., Wang, L., Ding, S., Yang, X. and Li, X.
(2022)
Few-Shot Classification With Feature Reconstruction Bias.
In: 2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), Chiang Mai, Thailand, 7-10 November 2022,
pp. 526-532.
ISBN 9781665486620
(doi: 10.23919/APSIPAASC55919.2022.9980086)
Song, Q., Peng, Z., Ji, L., Yang, X. and Li, X.
(2022)
Dual Prototypical Network for Robust Few-shot Image Classification.
In: 2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), Chiang Mai, Thailand, 7-10 November 2022,
pp. 533-537.
ISBN 9781665486620
(doi: 10.23919/APSIPAASC55919.2022.9979898)
Yang, X. , Guo, Y., Dong, M. and Xue, J.-H.
(2022)
Towards certified robustness of distance metric learning.
IEEE Transactions on Neural Networks and Learning Systems,
(doi: 10.1109/TNNLS.2022.3199902)
(PMID:36112549)
(Early Online Publication)
Lu, Y., Wang, B., Zhao, Y., Yang, X. , Li, L., Dong, M., Lv, Q., Zhou, F., Gu, N. and Shang, L.
(2022)
Physics-informed surrogate modeling for hydro-fracture geometry prediction based on deep learning.
Energy, 253,
124139.
(doi: 10.1016/j.energy.2022.124139)
2021
Li, X., Yu, L., Yang, X. , Ma, Z., Xue, J.-H., Cao, J. and Guo, J.
(2021)
ReMarNet: conjoint relation and margin learning for small-sample image classification.
IEEE Transactions on Circuits and Systems for Video Technology, 31(4),
pp. 1569-1579.
(doi: 10.1109/TCSVT.2020.3005807)
Yang, X. , Dong, M., Guo, Y. and Xue, J.-H.
(2021)
Metric Learning for Categorical and Ambiguous Features: An Adversarial Approach.
In: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2020), 14-18 Sep 2020,
pp. 223-238.
ISBN 9783030676605
(doi: 10.1007/978-3-030-67661-2_14)
2020
Li, X., Yan, J., Wu, J., Liu, Y., Yang, X. and Ma, Z.
(2020)
Anti-Noise Relation Network for Few-shot Learning.
In: 2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), Auckland, New Zealand, 07-10 Dec 2020,
pp. 1719-1724.
ISBN 9789881476883
Yang, X. , Dong, M., Wang, Z., Gao, L., Zhang, L. and Xue, J.-H.
(2020)
Data-augmented matched subspace detector for hyperspectral subpixel target detection.
Pattern Recognition, 106,
107464.
(doi: 10.1016/j.patcog.2020.107464)
Dong, M., Wang, Y., Yang, X. and Xue, J.-H.
(2020)
Learning local metrics and influential regions for classification.
IEEE Transactions on Pattern Analysis and Machine Intelligence, 42(6),
pp. 1522-1529.
(doi: 10.1109/TPAMI.2019.2914899)
Dong, M., Yang, X. , Zhu, R., Wang, Y. and Xue, J.-H.
(2020)
Generalization Bound of Gradient Descent for Non-Convex Metric Learning.
In: 34th Conference on Neural Information Processing Systems (NeurIPS 2020), 06-12 Dec 2020,
2019
Yang, X. , Zhang, L., Gao, L. and Xue, J.-H.
(2019)
MSDH: matched subspace detector with heterogeneous noise.
Pattern Recognition Letters, 125,
pp. 701-707.
(doi: 10.1016/j.patrec.2019.07.014)
This list was generated on Tue Mar 21 11:39:13 2023 GMT.