Dr Xiaochen Yang

  • Lecturer (Statistics)

Research interests

My research interests lie in statistical machine learning and image analysis. Past work includes developing target detection methods for hyperspectral images. Currently I am working on distance metric learning, improving methods towards better generalization in practically challenging scenarios, such as the few-shot regime and learning from weak supervision, and stronger (adversarial) robustness. I am interested in environmental and medical applications.

Research units

Publications

List by: Type | Date

Jump to: 2021 | 2020 | 2019
Number of items: 7.

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., Yang, X. , Zhu, R., Wang, Y. and Xue, J.-H. (2020) Generalization Bound of Gradient Descent for Non-Convex Metric Learning. In: Thirty-Fourth Conference on Neural Information Processing Systems (NeurIPS 2020), 06-12 Dec 2020, (In Press)

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)

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 Fri Jan 21 10:48:04 2022 GMT.
Jump to: Articles | Conference Proceedings
Number of items: 7.

Articles

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., 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)

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)

Conference Proceedings

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)

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

Dong, M., Yang, X. , Zhu, R., Wang, Y. and Xue, J.-H. (2020) Generalization Bound of Gradient Descent for Non-Convex Metric Learning. In: Thirty-Fourth Conference on Neural Information Processing Systems (NeurIPS 2020), 06-12 Dec 2020, (In Press)

This list was generated on Fri Jan 21 10:48:04 2022 GMT.

Supervision

  • Colombo, Pietro
    Methodological developments for accounting for uncertainty within environmental data
  • Mandal, Adhiraj
    Robust COVID Mortality score using Demographics, lab results and Imaging§

Teaching

Statistics 2Y: Regression modelling (STATS2006)

Data mining (STATS5099)

Additional information

I am currently looking for highly motivated PhD students. Please email me if you are interested.