贾育衡

发布者:贾育衡发布时间:2020-11-14浏览次数:1901

Yuheng Jia(贾育衡)

Ph.D., Associate Professor 

School of Computer Science and Engineering, Southeast University

I am a member of PAttern Learning and Mining(PALM) Lab. 


贾育衡, 博士,副教授。2019年获得香港城市大学(CityU)博士学位,2019-2020年任香港城市大学博士后研究员。 导师为Sam Kwong 讲席教授。2020年起在东南大学计算机科学与工程学院任职副教授。现为东南大学PALM实验室成员。曾任斯坦福大学(Stanford University)访问学者(2018年)。研究内容广泛涉及机器学习和数据表示的多个子领域,主要包括高维数据分析与建模、张量表示与建模、图机器学习等,以及相关的一些应用。在相关研究领域的国际会议和期刊上发表学术论文近40篇,其中CCF-A/IEEE Trans 论文近20篇。担任多个国际著名期刊会议的程序委员会委员和审稿人。


My research interests broadly include topics in machine learning and data representation, such as high-dimensional data modeling and analysis, low-rank tensor/matrix approximation and factorization, and graph signal processing and machine learning on graphs, as well as some related applications. I have published about 40 peer-reviewed papers on top-tier journals and conferences with respect to those topics.  I defended my thesis on Nov. 2018 and officially received the Ph.D. degree on Feb. 2019 from the Computer Science Department at the City University of Hong Kong, where I was advised by Professor Sam Kwong.


计划每年辅导2-3名本科生进行科研训练,欢迎有兴趣的同学报名!


Contact Information:

Office: Room 230, School of Computer Science and Engineering, Southeast University Jiulonghu Campus, Nanjing, Jiangsu, China. (东南大学九龙湖校区,计算机楼,230房间)

Email: yhjia at seu dot edu dot cn


Selective Publications:(# Corresponding author, * Co-first author)

Journal Papers: 

  • Y. Jia, H. Liu. J. Hou, S. Kwong, Q. Zhang, Multi-View Spectral Clustering Tailored Tensor Low-Rank Representation, IEEE Transactions on Circuits and Systems for Video Technology (IEEE TCSVT), 2021, in press, code.

  • Y. Jia, H. Liu. J. Hou, S. Kwong, Q. Zhang, Semi-supervised Affinity Matrix Learning via Dual-channel Information Recovery, IEEE Transactions on Cybernetics (IEEE TCyb), 2020, in press, code.

  • H. Li, Y. Jia #, R. Cong, W. Wu, S. Kwong, C. Chen, Superpixel Segmentation Based on Spatially Constrained Subspace Clustering, IEEE Transactions on  Industrial Informatics (IEEE TII), 2020, in press. 

  • W. Wu, Y. Jia, S. Wang, R. Wang, H. Fan, S. Kwong, Positive and Negative Label-Driven Nonnegative Matrix Factorization, IEEE Transactions on Circuits and Systems for Video Technology (IEEE TCSVT), 2020, in press.

  • Z. Peng, Y. Jia, J. Hou, Non-Negative Transfer Learning with Consistent Inter-domain Distribution, IEEE Signal Processing Letters (IEEE SPL), vol. 27, pp. 1720-1724, 2020.

  • R. Wang, S. Kwong, X. Wang, Y. Jia, Active k-Labelsets Ensemble for Multi-label Classification, Pattern Recognition (PR), vol. 109, pp. 107583, 2021.

  • Y. Jia, W. Wu, R. Wang, J. Hou, S. Kwong, Joint Optimization for Pairwise Constraint Propagation, IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2020, in press, code.

  • Y. Jia, J. Hou, S. Kwong, Constrained Clustering with Dissimilarity Propagation Guided Graph-Laplacian PCA, IEEE Transactions on Neural Networks and Learning Systems, (IEEE TNNLS), 2020, in press, code.

  • Y. Jia, H. Liu, J. Hou, S. Kwong, Clustering-aware Graph Construction: A Joint Learning Perspective, IEEE Transactions on Signal and Information Processing over Networks (IEEE TSIPN), vol. 6, pp. 357-370, 2020.

  • Y. Jia, H. Liu, J. Hou, S. Kwong, Semi-supervised Adaptive Symmetric Nonnegative Matrix Factorization, IEEE Transactions on Cybernetics (IEEE TCyb), 2020 in press, code.

  • S. Yang, J. Hou, Y. Jia, S. Mei, Q. Du, Hyperspectral Image Classification with Incremental Sparse Representation, IEEE Geoscience and Remote Sensing Letters (IEEE GRSL), vol. 17, no. 9, pp. 1598-1602, 2020.

  • Y. Jia, H. Liu, J. Hou, S. Kwong, Pairwise Constraint Propagation with Dual Adversarial Manifold Regularization, IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2020, vol. 31, no. 12, pp. 5575-5587, 2020, code.

  • Y. Jia, S. Kwong, J. Hou, W. Wu, Semi-Supervised Non-Negative Matrix Factorization with Dissimilarity and Similarity Regularization, IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), vol. 31, no. 7, pp. 2510-2521, 2020, code.

  • Y. Jia, S. Kwong, J. Hou, Semi-Supervised Spectral Clustering with Structured Sparsity Regularization, IEEE Signal Processing Letters (IEEE SPL), vol. 25, no. 3, pp. 403-407, 2018, code.

  • Y. Jia, S. Kwong, W. Wu, R. Wang, W. Gao, Sparse Bayesian Learning Based Kernel Poisson Regression, IEEE Transactions on Cybernetics (IEEE TCyb), vol. 49, no. 1, pp. 56-68, 2019.

  • Y. Jia, S. Kwong, R. Wang, Applying Exponential Family Distribution to Generalized Extreme Learning Machine, IEEE Transactions on Systems, Man, and Cybernetics: Systems (IEEE TSMC), vol. 50, no. 5, pp. 1794-1804, 2020.

  • W. Wu, Y. Jia, S. Kwong, J. Hou, Pairwise Constraint Propagation Induced Symmetric Nonnegative Matrix Factorization, IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), vol. 29, no. 12, pp. 6348-6361, 2018, code.

  • W. Gao, S. Kwong, Y. Jia, Joint Machine Learning and Game Theory for Rate Control in High Efficiency Video Coding, IEEE Transactions on Image Processing (IEEE TIP), vol. 26, no. 12, pp. 6074-6089, 2017.

  • J. Zhang, S. Kwong, Y. Jia, K. Wong, NSSRF: global network similarity search with subgraph signatures and its applications, Bioinformatics,  vol. 33, no. 11, pp. 1696-1702, 2017.

  • H. Li, S. Kwong, C. Chen, Y. Jia, R. Cong, Superpixel Segmentation Based on Square-wise Asymmetric Partition and Structural Approximation, IEEE Transactions on Multimedia (IEEE TMM), vol. 21, no. 10, pp. 2625-2637, 2019.

  • W. Wu, S. Kwong, Y. Zhou, Y. Jia, W. Gao, Nonnegative Matrix Factorization with Mixed Hypergraph Regularization for Community Detection, Information Sciences, Vol. 435, pp. 263-281, 2018.

  • W. Wu, S. Kwong, J. Hou, Y. Jia, H. Ip, Simultaneous Dimensionality Reduction and Classification via Dual Embedding Regularized Nonnegative Matrix Factorization, IEEE Transactions on Image Processing (IEEE TIP), vol. 28, no. 8, pp. 3836-3847, 2019, code.

  • S. Yang, J. Hou, Y. Jia, S.Mei, Q.Du, Pseudo-Label Guided Kernel Learning for Hyper-spectral Image Classification, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (IEEE JSTAEORS),  vol. 12, no. 3, pp. 1000-1011, 2019, code on Google drive.


Conference Papers:

  • Y. Jia, H. Liu, J. Hou, Qingfu Zhang, Clustering Ensemble Meets Low-rank Tensor Approximation, AAAI, 2021, code.

  • H. Liu, Y. Jia *, J. Hou, Q. Zhang, Imbalance-aware Pairwise Constraint Propagation, ACM MM, 2019.

  • Y. Jia, S. Kwong, J. Hou, W. Wu, Convex Constrained Clustering with Graph-Laplacian PCA, IEEE ICME, 2018.

  • Y. Jia, S. Kwong, W. Wu, W. Gao, R. Wang, Generalized Relevance Vector Machine, IntelliSys, 2017.

  • R. Wang, S. Kwong, Y. Jia, Z. Huang, L. Wu, Mutual Information Based K-Labelsets Ensemble for Multi-Label Classification, FUZZ-IEEE, 2018.

  • M. Wu, S. Kwong, Y. Jia, K. Li, Q. Zhang, Adaptive Weights Generation for Decomposition-based Multi-objective Optimization Using Gaussian Process Regression, GECCO, 2017.

  • W. Gao, S. Kwong, Y. Zhou, Y. Jia, et al., Multiscale Phase Congruency Analysis for Image Edge Visual Saliency Detection, ICMLC, 2016.


See the full publications on Google Scholar or my personal homepage.


Teaching:

Graduate course

Artificial intelligence(人工智能), 2021 Spring