Research interests
My research interests lie in statistical machine learning and image analysis. Past works include distance metric learning and target detection for hyperspectral images. The ongoing research topics include: (1) machine learning under data paucity (or learning with small data): few-shot learning, self-supervised learning, domain adaptation; (2) trustworthy machine learning: adversarial attacks and defenses, uncertainty quantification, interpretability; (3) machine learning for medical and healthcare applications: medical image analysis, disease detection and diagnosis, disease progression modeling.
Personal webpage: https://xiao-chen-yang.github.io/
Research groups
Publications
2025
Li, Xiaoxu, Ding, Shuo, Xie, Jiyang, Yang, Xiaochen ORCID: https://orcid.org/0000-0002-9299-5951, Ma, Zhanyu and Xue, Jing-Hao
(2025)
CDN4: A cross-view Deep Nearest Neighbor Neural Network for fine-grained few-shot classification.
Pattern Recognition, 163,
111466.
(doi: 10.1016/j.patcog.2025.111466)
Wang, Xiaoke, Yang, Xiaochen ORCID: https://orcid.org/0000-0002-9299-5951, Zhu, Rui and Xue, Jing-Hao
(2025)
PUAL: a classifier on trifurcate positive-unlabeled data.
Neurocomputing,
(Accepted for Publication)
Dong, Yanni, Zhu, Bei, Yang, Xiaochen ORCID: https://orcid.org/0000-0002-9299-5951 and Ma, Xin
(2025)
Deep metric learning based on Brownian covariance representation for few-shot hyperspectral image classification.
IEEE Transactions on Geoscience and Remote Sensing,
(doi: 10.1109/TGRS.2025.3549633)
(Early Online Publication)
Wang, C. et al. (2025) Denoising reuse: exploiting inter-frame motion consistency for efficient video generation. IEEE Transactions on Circuits and Systems for Video Technology, (doi: 10.1109/TCSVT.2025.3548728) (Early Online Publication)
Colombo, Pietro, Miller, Claire ORCID: https://orcid.org/0000-0002-1857-4454, Yang, Xiaochen
ORCID: https://orcid.org/0000-0002-9299-5951, O'Donnell, Ruth
ORCID: https://orcid.org/0000-0002-3538-7511 and Maranzano, Paolo
(2025)
Warped multifidelity Gaussian processes for data fusion of skewed environmental data.
Journal of the Royal Statistical Society: Series C (Applied Statistics),
(Accepted for Publication)
Dong, Yanni, Yang, Xiaochen ORCID: https://orcid.org/0000-0002-9299-5951 and Du, Qian (Eds.)
(2025)
Artificial Intelligence-Driven Methods for Remote Sensing Target and Object Detection.
MDPI.
ISBN 9783725832316
2024
Dong, F. et al. (2024) Once Read is Enough: Domain-specific Pretraining-free Language Models with Cluster-guided Sparse Experts for Long-tail Domain Knowledge. In: 38th Annual Conference on Neural Information Processing Systems (NeurIPS 2024), Vancouver, Canada, 9-15 December 2024, (Accepted for Publication)
Li, Xiaoxu, Li, Zhen, Xie, Jiyang, Yang, Xiaochen ORCID: https://orcid.org/0000-0002-9299-5951, Xue, Jing-Hao and Ma, Zhanyu
(2024)
Self-reconstruction network for fine-grained few-shot classification.
Pattern Recognition, 153,
110485.
(doi: 10.1016/j.patcog.2024.110485)
Di Campli San Vito, P. et al. (2024) RadioMe: Adaptive Radio with Music Intervention and Reminder System for People with Dementia in Their Own Home. In: Augmented Humans 2024, Melbourne, Australia, 4-6 April 2024, ISBN 9798400709807 (doi: 10.1145/3652920.3653055)
Yang, Xiaochen ORCID: https://orcid.org/0000-0002-9299-5951, Guo, Yiwen, Dong, Mingzhi and Xue, Jing-Hao
(2024)
Towards certified robustness of distance metric learning.
IEEE Transactions on Neural Networks and Learning Systems, 35(3),
pp. 3834-3844.
(doi: 10.1109/TNNLS.2022.3199902)
(PMID:36112549)
Dong, Yanni, Yang, Xiaochen ORCID: https://orcid.org/0000-0002-9299-5951 and Du, Qian (Eds.)
(2024)
Artificial Intelligence-Driven Methods for Remote Sensing Target and Object Detection.
Remote Sensing.
[Edited Journal]
2023
Cheng, Fangqi and Yang, Xiaochen ORCID: https://orcid.org/0000-0002-9299-5951
(2023)
Self-Supervised Cross-Encoder for Diagnosis of Alzheimer's Disease.
37th annual conference on Neural Information Processing Systems, New Orleans, Louisiana, USA, 10-16 Dec 2023.
(Accepted for Publication)
Di Campli San Vito, Patrizia ORCID: https://orcid.org/0000-0002-2499-8464, Shakeri, Gözel, Ross, James, Yang, Xiaochen
ORCID: https://orcid.org/0000-0002-9299-5951 and Brewster, Stephen
ORCID: https://orcid.org/0000-0001-9720-3899
(2023)
Development of a Real-Time Stress Detection System for Older Adults with Heart Rate Data.
In: 16th International Conference on PErvasive Technologies Related to Assistive Environments (PETRA '23), Corfu, Greece, 5-7 Jul 2023,
ISBN 9798400700699
(doi: 10.1145/3594806.3594817)
Colombo, Pietro, Miller, Claire ORCID: https://orcid.org/0000-0002-1857-4454, O'Donnell, Ruth
ORCID: https://orcid.org/0000-0002-3538-7511 and Yang, Xiaochen
ORCID: https://orcid.org/0000-0002-9299-5951
(2023)
A Multifidelity Framework for Wind Speed Data.
In: 37th International Workshop on Statistical Modelling (IWSM), Dortmund, Germany, 16-21 Jul 2023,
ISBN 9783947323425
Di Campli San Vito, P. et al. (2023) RadioMe: Adaptive Radio to Support People with Mild Dementia in Their Own Home. In: Second International Conference on Hybrid Human-Artificial Intelligence (HHAI 2023), Munich, Germany, 26-30 June 2023, pp. 413-415. ISBN 9781643683942 (doi: 10.3233/FAIA230114)
Li, Xiaoxu, Yang, Xiaochen ORCID: https://orcid.org/0000-0002-9299-5951, Ma, Zhanyu and Xue, Jing-Hao
(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,
Shi, Y. et al. (2023) Train Faster, Perform Better: Modular Adaptive Training in Over-Parameterized Models. In: 37th Annual Conference on Neural Information Processing Systems (NeurIPS 2023), New Orleans, Louisiana, USA, 10-16 Dec 2023,
2022
Li, Zhen, Wang, Lang, Ding, Shuo, Yang, Xiaochen ORCID: https://orcid.org/0000-0002-9299-5951 and Li, Xiaoxu
(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, Qi, Peng, Zebin, Ji, Luchen, Yang, Xiaochen ORCID: https://orcid.org/0000-0002-9299-5951 and Li, Xiaoxu
(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)
Lu, Yutian, Wang, Bo, Zhao, Yingying, Yang, Xiaochen ORCID: https://orcid.org/0000-0002-9299-5951, Li, Lizhe, Dong, Mingzhi, Lv, Qin, Zhou, Fujian, Gu, Ning and Shang, Li
(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, Xiaoxu, Yu, Liyun, Yang, Xiaochen ORCID: https://orcid.org/0000-0002-9299-5951, Ma, Zhanyu, Xue, Jing-Hao, Cao, Jie and Guo, Jun
(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, Xiaochen ORCID: https://orcid.org/0000-0002-9299-5951, Dong, Mingzhi, Guo, Yiwen and Xue, Jing-Hao
(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, Xiaoxu, Yan, Jintao, Wu, Jijie, Liu, Yuxin, Yang, Xiaochen ORCID: https://orcid.org/0000-0002-9299-5951 and Ma, Zhanyu
(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, Xiaochen ORCID: https://orcid.org/0000-0002-9299-5951, Dong, Mingzhi, Wang, Ziyu, Gao, Lianru, Zhang, Lefei and Xue, Jing-Hao
(2020)
Data-augmented matched subspace detector for hyperspectral subpixel target detection.
Pattern Recognition, 106,
107464.
(doi: 10.1016/j.patcog.2020.107464)
Dong, Mingzhi, Wang, Yujiang, Yang, Xiaochen ORCID: https://orcid.org/0000-0002-9299-5951 and Xue, Jing-Hao
(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, Mingzhi, Yang, Xiaochen ORCID: https://orcid.org/0000-0002-9299-5951, Zhu, Rui, Wang, Yujiang and Xue, Jing-Hao
(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, Xiaochen ORCID: https://orcid.org/0000-0002-9299-5951, Zhang, Lefei, Gao, Lianru and Xue, Jing-Hao
(2019)
MSDH: matched subspace detector with heterogeneous noise.
Pattern Recognition Letters, 125,
pp. 701-707.
(doi: 10.1016/j.patrec.2019.07.014)
Articles
Li, Xiaoxu, Ding, Shuo, Xie, Jiyang, Yang, Xiaochen ORCID: https://orcid.org/0000-0002-9299-5951, Ma, Zhanyu and Xue, Jing-Hao
(2025)
CDN4: A cross-view Deep Nearest Neighbor Neural Network for fine-grained few-shot classification.
Pattern Recognition, 163,
111466.
(doi: 10.1016/j.patcog.2025.111466)
Wang, Xiaoke, Yang, Xiaochen ORCID: https://orcid.org/0000-0002-9299-5951, Zhu, Rui and Xue, Jing-Hao
(2025)
PUAL: a classifier on trifurcate positive-unlabeled data.
Neurocomputing,
(Accepted for Publication)
Dong, Yanni, Zhu, Bei, Yang, Xiaochen ORCID: https://orcid.org/0000-0002-9299-5951 and Ma, Xin
(2025)
Deep metric learning based on Brownian covariance representation for few-shot hyperspectral image classification.
IEEE Transactions on Geoscience and Remote Sensing,
(doi: 10.1109/TGRS.2025.3549633)
(Early Online Publication)
Wang, C. et al. (2025) Denoising reuse: exploiting inter-frame motion consistency for efficient video generation. IEEE Transactions on Circuits and Systems for Video Technology, (doi: 10.1109/TCSVT.2025.3548728) (Early Online Publication)
Colombo, Pietro, Miller, Claire ORCID: https://orcid.org/0000-0002-1857-4454, Yang, Xiaochen
ORCID: https://orcid.org/0000-0002-9299-5951, O'Donnell, Ruth
ORCID: https://orcid.org/0000-0002-3538-7511 and Maranzano, Paolo
(2025)
Warped multifidelity Gaussian processes for data fusion of skewed environmental data.
Journal of the Royal Statistical Society: Series C (Applied Statistics),
(Accepted for Publication)
Li, Xiaoxu, Li, Zhen, Xie, Jiyang, Yang, Xiaochen ORCID: https://orcid.org/0000-0002-9299-5951, Xue, Jing-Hao and Ma, Zhanyu
(2024)
Self-reconstruction network for fine-grained few-shot classification.
Pattern Recognition, 153,
110485.
(doi: 10.1016/j.patcog.2024.110485)
Yang, Xiaochen ORCID: https://orcid.org/0000-0002-9299-5951, Guo, Yiwen, Dong, Mingzhi and Xue, Jing-Hao
(2024)
Towards certified robustness of distance metric learning.
IEEE Transactions on Neural Networks and Learning Systems, 35(3),
pp. 3834-3844.
(doi: 10.1109/TNNLS.2022.3199902)
(PMID:36112549)
Li, Xiaoxu, Yang, Xiaochen ORCID: https://orcid.org/0000-0002-9299-5951, Ma, Zhanyu and Xue, Jing-Hao
(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)
Lu, Yutian, Wang, Bo, Zhao, Yingying, Yang, Xiaochen ORCID: https://orcid.org/0000-0002-9299-5951, Li, Lizhe, Dong, Mingzhi, Lv, Qin, Zhou, Fujian, Gu, Ning and Shang, Li
(2022)
Physics-informed surrogate modeling for hydro-fracture geometry prediction based on deep learning.
Energy, 253,
124139.
(doi: 10.1016/j.energy.2022.124139)
Li, Xiaoxu, Yu, Liyun, Yang, Xiaochen ORCID: https://orcid.org/0000-0002-9299-5951, Ma, Zhanyu, Xue, Jing-Hao, Cao, Jie and Guo, Jun
(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, Xiaochen ORCID: https://orcid.org/0000-0002-9299-5951, Dong, Mingzhi, Wang, Ziyu, Gao, Lianru, Zhang, Lefei and Xue, Jing-Hao
(2020)
Data-augmented matched subspace detector for hyperspectral subpixel target detection.
Pattern Recognition, 106,
107464.
(doi: 10.1016/j.patcog.2020.107464)
Dong, Mingzhi, Wang, Yujiang, Yang, Xiaochen ORCID: https://orcid.org/0000-0002-9299-5951 and Xue, Jing-Hao
(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, Xiaochen ORCID: https://orcid.org/0000-0002-9299-5951, Zhang, Lefei, Gao, Lianru and Xue, Jing-Hao
(2019)
MSDH: matched subspace detector with heterogeneous noise.
Pattern Recognition Letters, 125,
pp. 701-707.
(doi: 10.1016/j.patrec.2019.07.014)
Edited Books
Dong, Yanni, Yang, Xiaochen ORCID: https://orcid.org/0000-0002-9299-5951 and Du, Qian (Eds.)
(2025)
Artificial Intelligence-Driven Methods for Remote Sensing Target and Object Detection.
MDPI.
ISBN 9783725832316
Edited Journals
Dong, Yanni, Yang, Xiaochen ORCID: https://orcid.org/0000-0002-9299-5951 and Du, Qian (Eds.)
(2024)
Artificial Intelligence-Driven Methods for Remote Sensing Target and Object Detection.
Remote Sensing.
[Edited Journal]
Conference or Workshop Item
Cheng, Fangqi and Yang, Xiaochen ORCID: https://orcid.org/0000-0002-9299-5951
(2023)
Self-Supervised Cross-Encoder for Diagnosis of Alzheimer's Disease.
37th annual conference on Neural Information Processing Systems, New Orleans, Louisiana, USA, 10-16 Dec 2023.
(Accepted for Publication)
Conference Proceedings
Dong, F. et al. (2024) Once Read is Enough: Domain-specific Pretraining-free Language Models with Cluster-guided Sparse Experts for Long-tail Domain Knowledge. In: 38th Annual Conference on Neural Information Processing Systems (NeurIPS 2024), Vancouver, Canada, 9-15 December 2024, (Accepted for Publication)
Di Campli San Vito, P. et al. (2024) RadioMe: Adaptive Radio with Music Intervention and Reminder System for People with Dementia in Their Own Home. In: Augmented Humans 2024, Melbourne, Australia, 4-6 April 2024, ISBN 9798400709807 (doi: 10.1145/3652920.3653055)
Di Campli San Vito, Patrizia ORCID: https://orcid.org/0000-0002-2499-8464, Shakeri, Gözel, Ross, James, Yang, Xiaochen
ORCID: https://orcid.org/0000-0002-9299-5951 and Brewster, Stephen
ORCID: https://orcid.org/0000-0001-9720-3899
(2023)
Development of a Real-Time Stress Detection System for Older Adults with Heart Rate Data.
In: 16th International Conference on PErvasive Technologies Related to Assistive Environments (PETRA '23), Corfu, Greece, 5-7 Jul 2023,
ISBN 9798400700699
(doi: 10.1145/3594806.3594817)
Colombo, Pietro, Miller, Claire ORCID: https://orcid.org/0000-0002-1857-4454, O'Donnell, Ruth
ORCID: https://orcid.org/0000-0002-3538-7511 and Yang, Xiaochen
ORCID: https://orcid.org/0000-0002-9299-5951
(2023)
A Multifidelity Framework for Wind Speed Data.
In: 37th International Workshop on Statistical Modelling (IWSM), Dortmund, Germany, 16-21 Jul 2023,
ISBN 9783947323425
Di Campli San Vito, P. et al. (2023) RadioMe: Adaptive Radio to Support People with Mild Dementia in Their Own Home. In: Second International Conference on Hybrid Human-Artificial Intelligence (HHAI 2023), Munich, Germany, 26-30 June 2023, pp. 413-415. ISBN 9781643683942 (doi: 10.3233/FAIA230114)
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,
Shi, Y. et al. (2023) Train Faster, Perform Better: Modular Adaptive Training in Over-Parameterized Models. In: 37th Annual Conference on Neural Information Processing Systems (NeurIPS 2023), New Orleans, Louisiana, USA, 10-16 Dec 2023,
Li, Zhen, Wang, Lang, Ding, Shuo, Yang, Xiaochen ORCID: https://orcid.org/0000-0002-9299-5951 and Li, Xiaoxu
(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, Qi, Peng, Zebin, Ji, Luchen, Yang, Xiaochen ORCID: https://orcid.org/0000-0002-9299-5951 and Li, Xiaoxu
(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, Xiaochen ORCID: https://orcid.org/0000-0002-9299-5951, Dong, Mingzhi, Guo, Yiwen and Xue, Jing-Hao
(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, Xiaoxu, Yan, Jintao, Wu, Jijie, Liu, Yuxin, Yang, Xiaochen ORCID: https://orcid.org/0000-0002-9299-5951 and Ma, Zhanyu
(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, Mingzhi, Yang, Xiaochen ORCID: https://orcid.org/0000-0002-9299-5951, Zhu, Rui, Wang, Yujiang and Xue, Jing-Hao
(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,
Supervision
- Colombo, Pietro
Methodological developments for accounting for uncertainty within environmental data - Mandal, Adhiraj
An Investigation into Distribution of Random Functions and Model-Based Clustering for Functional Data
Teaching
Statistics 2Y: Regression Modelling (STATS2006)
Data Mining and Machine Learning (STATS5099)
Additional information
I am currently looking for highly motivated PhD students. Please read the following page for more information.