Email: pengyang5612@gmail.com
My Curriculum Vitae can be found here.
My Good Scholar can be found here.
Research
My current research interests include:
Data Mining: graph-based learning, classification; network data; recommender system; clustering
Machine Learning: online continual learning, meta-learning, multi-task learning, active learning, kernelized optimization.
Bioinformatics: disease gene identification; drug-target interaction prediction; fusion method; predictive model
Publications
Ongoing work: (1) Imbalanced Learning (2) Multi-lingual Transfer Learning (3) Reinforcement Learning
Submitted work
2021-2022
[F] Peng Yang, Shaogang Ren, Ping Li. "Calibrating CNNs for Few-Shot Meta Learning" Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV 2022)
[F] Peng Yang, Yingjie Lao, Ping Li. "Robust Watermarking for Deep Neural Networks via Bi-level Optimization" Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV 2021): 14841-14850.
[F] Doan Khoa, Peng Yang, Ping Li. "Discrete Wasserstein Distributional Matching for Quantization in Image Hashing" Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2022)
[F] Haiyan Yin*, Peng Yang*, Ping Li. "Mitigating Forgetting in Online Continual Learning with Neuron Calibration" The proceeding of Advances in Neural Information Processing (NeuIPS 2021) (*: Equal Contribution) [Code] (For code issue, please email: pengyang5612@gmail.com)
[F] Peng Yang, Xiaoyun Li, Ping Li. "Graph-based Adversarial Online Kernel Learning with Adaptive Embedding" The IEEE International Conference on Data Mining (ICDM 2021)
[F] Yingjie Lao*, Peng Yang*, Weijie Zhao, Ping Li. "Identification for Deep Neural Network: Simply Adjusting Few Weights!" The IEEE International Conference on Data Engineering (ICDE 2022)
[F] Yingjie Lao, Weijie Zhao, Peng Yang, Ping Li. "DeepAuth: A DNN Authentication Framework by Model-Unique and Fragile Signature Embedding" The Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI-22)
[F] Peng Yang, Ping Li. "Adversarial Kernel Sampling on Class-imbalanced Data Streams" Proceedings of the 30th ACM International Conference on Information and Knowledge Management (CIKM 2021): 2352-2362.
[F] Xin Wang, Peng Yang, Shaopeng Chen, Lin Liu, Lian Zhao, Jiacheng Guo, Mingming Sun, Ping Li "Efficient Learning to Learn a Robust CTR Model for Web-scale Online Sponsored Search Advertising" Proceedings of the 30th ACM International Conference on Information and Knowledge Management (CIKM 2021): 4203–4213.
[J] Remin Han, Li Liu, Peng Yang, Fa Zhang, Xin Gao. "A novel constrained reconstruction model towards high-resolution subtomogram averaging" Bioinformatics 37, no. 11 (2021): 1616-1626.
2020
[F] Peng Yang, Ping Li: "Adaptive Online Kernel Sampling for Vertex Classification" International Conference on Artificial Intelligence and Statistics (AISTATS 2020).
[F] Peng Yang, Ping Li: "Distributed Primal-Dual Optimization for Online Multi-task Learning" AAAI Conference on Artificial Intelligence (AAAI 2020).
[S] Peng Yang, Ping Li: "Efficient Online Multi-Task Learning via Adaptive Kernel Selection" The WEB Conference (WWW 2020).
2019
[F] Peng Yang, Peilin Zhao, Jiayu Zhou, Xin Gao: "Confidence Weighted Multitask Learning" AAAI Conference on Artificial Intelligence (AAAI 2019).
[F] Peng Han*, Peng Yang*, Peilin Zhao, Shuo Shang, Yong Liu, Jiayu Zhou, Xin Gao, Panos Kalnis: "GCN-MF: Disease-Gene Association Identification By Graph Convolutional Networks and Matrix Factorzation" ACM SIGKDD Conference On Knowledge Discovery and Data Mining (KDD 2019) (*: Equal Contribution). [Code]
[F] Lizhong Ding, Shizhong Liao, Yong Liu, Peng Yang, Yu Li, Yijie Pan, Chao Huang, Ling Shao, Xin Gao: "Approximate Kernel Selection with Strong Approximate Consistency" AAAI Conference on Artificial Intelligence (AAAI 2019).
[F] Lizhong Ding, Zhi Liu, Yu Li, Shizhong Liao, Yong Liu, Peng Yang, Ge Yu, Ling Shao, Xin Gao: "Linear Kernel Tests via Empirical Likelihood for High Dimensional Data" AAAI Conference on Artificial Intelligence (AAAI 2019).
[J] Guangxia Li, Peilin Zhao, Tao Mei, Peng Yang, Yulong Shen, Kuiyu Chang, Steven C. H. Hoi: "Collaborative Online Ranking Algorithms for Multitask Learning" Knowledge and Information Systems (KAIS) journal.
[F] Yu Li, Hiroyuki Kuwahara, Peng Yang, Le Song, Xin Gao: "PGCN: Disease gene prioritization by disease and gene embedding through graph convolutional neural networks" bioRxiv, 532226.
2018
[F] Peng Yang, Peilin Zhao, Xin Gao: "Bandit Online Learning on Graphs via Adaptive Optimization" International Joint Conference on Artificial Intelligence and European Conference on Artificial Intelligence (IJCAI 2018).
[S] Peng Yang, Peilin Zhao, Vincent Zheng, Lizhong Ding, Xin Gao: "Robust Asymmetric Recommendation via Min-Max Optimization" ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2018).
[F] Peng Yang, Peilin Zhao, Yong Liu, Xin Gao: "Robust Cost-Sensitive Learning for Recommendation with Implicit Feedback" SIAM International Conference on Data Mining (SDM 2018).
[F] Lizhong Ding, Shizhong Liao, Yong Liu, Peng Yang, Xin Gao: "Random Kernel Selection via Spectra of Multilevel Circulant Matrices" AAAI Conference on Artificial Intelligence (AAAI 2018).
[J] Renmin Han, Xiaohua Wan, Lun Li, Alber Lawrence, Peng Yang, Yu Li, Sheng Wang, Fei Sun, Zhiyong Liu, Xin Gao, Fa Zhang: "AuTom-dualx: a toolkit for fully automatic alignment of dual-axis tilt series with simultaneous reconstruction" Bioinformatics, 2018.
[J] Yu Li, Zhongxiao Li, Lizhong Ding, Peng Yang, Yuhui Hu, Wei Chen, Xin Gao: "SupportNet: solving catastrophic forgetting in class incremental learning with support data" 2019.
2017
[J] Peng Yang, Peilin Zhao, Xin Gao: "Robust Online Multi-Task Learning with Correlative and Personalized Structures" IEEE Transactions on Knowledge and Data Engineering (TKDE 2017).
[F] Sujatha Das Gollapalli, Xiao-Li Li, Peng Yang: "Incorporating Expert Knowledge into Keyphrase Extraction" AAAI Conference on Artificial Intelligence (AAAI 2017).
[J] Jing Guo, Hao Chen, Peng Yang, YT Lee, M Wu, T Przytycka, CK Kwoh, J Zheng: "LDSplitDB: A database for studies of meiotic recombination hotspots in MHC using human genomic data" BMC Medical Genomics (GIW/BIOINFO 2017) In press.
[P] Haozhi Huang, Hao Wang, Wenhan Luo, Lin Ma, Peng Yang, Wenhao Jiang, Xiaolong Zhu, Wei Liu: "Real-Time Neural Method for Video Style Transfer" IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2017).
2016
[F] Peng Yang, Peilin Zhao, Zhen Hai, Wei Liu, Steven C.H. Hoi, Xiaoli Li: "Efficient Multi-Class Selective Sampling on Graphs" Conference on Uncertainty in Artificial Intelligence (UAI 2016).
[F] Peng Yang, Guangxia Li, Peilin Zhao, Xiaoli Li, Sujatha Das Gollapalli: "Learning Correlative and Personalized Structure for Online Multi-Task Classification" SIAM International Conference on Data Mining (SDM 2016).
[F] Zhen Hai, Peilin Zhao, Peng Cheng, Peng Yang, Xiaoli Li, Guangxia Li: "Deceptive Review Spam Detection via Exploiting Task Relatedness and Unlabeled Data" Conference on Empirical Methods in Natural Language Processing (EMNLP 2016).
2015
[F] Peng Yang, Peilin Zhao, Vincent W. Zheng, Xiao-Li LI: "An Aggressive Graph-based Selective Sampling Algorithm for Classification" IEEE International Conference on Data Mining (ICDM 2015). (Long Paper Accepted Rate: 8.4%)
[F] Peng Yang, Peilin Zhao: "A Min-Max Optimization Framework for Online Graph Classification" ACM Conference on Information and Knowledge Management (CIKM 2015). [Code]
[J] Hao Chen, Peng Yang, Jing Guo, Chee Keong Kwoh, Teresa M Przytycka, Jie Zheng: "ARG-walker: inference of individual specific strengths of meiotic recombination hotspots by population genomics analysis" BMC genomics, 2015.
2014
[J] Peng Yang, Xiaoli Li, Hon-Nian Chua, Chee-Keong Kwoh, See-Kiong Ng: "Ensemble positive unlabeled learning for disease gene identification" PloS one 2014.
[J] Peng Yang, Min Wu, Jing Guo, Chee-Keong Kwoh, M. Teresa Przytycka, Jie. Zheng: "LDsplit: screening for cis-regulatory motifs stimulating meiotic recombination hotspots by analysis of DNA sequence polymorphisms" BMC bioinformatics, 2014.
[J] Peng Yang, Xiaoquan Su, Le Ou-Yang, Hon-Nian Chua, Xiao-Li Li, Kang Ning: "Microbial community pattern detection in human body habitats via ensemble clustering framework" BMC systems biology, 2014.
[T] Peng Yang: "Computational Approaches for Disease Gene Identification" arXiv preprint arXiv:1704.03548.
[J] Jing Guo, Ritika Jain, Peng Yang, Rui Fan, Chee Keong Kowh, Jie Zheng: "Reliable and Fast Estimation of Recombination Rates by Convergence Diagnosis and Parallel Markov Chain Monte Carlo" IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), 2014.
[J] Pamela Thompson, Kevin Urayama, Jie Zheng, Peng Yang, Matt Ford, Patricia Buffler, Anand Chokkalingam, Tracy Lightfoot, Malcolm Taylor: "Differences in Meiotic Recombination Rates in Childhood Acute Lymphoblastic Leukemia at an MHC Class II Hotspot Close to Disease Associated Haplotypes" PloS one, 2014.
[J] Le Ou-Yang, Dao-Qing Dai, Xiao-Li Li, Min Wu, Xiao-Fei Zhang, Peng Yang: "Detecting temporal protein complexes from dynamic protein-protein interaction networks" BMC bioinformatics, 2014
[F] Wei Wu, Yue Wang, JB Gomes, DT Anh, Spiros Antonatos, Mingqiang Xue, Peng Yang, Ghim Eng Yap, et al: "Oscillation Resolution for Mobile Phone Cellular Tower Data to Enable Mobility Modelling" IEEE 15th International Conference on Mobile Data Management (MDM-2014).
2013
[J] Jianping Mei, Chee-Keong Kwoh, Peng Yang, Xiao-Li Li, Jie Zheng: "Drug-Target Interaction Prediction by Learning From Local Information and Neighbors" Bioinformatics, 2013.
2012
[J] Peng Yang, Xiao-Li Li, Jian-Ping Mei, Chee-Keong Kwoh, See-Kiong Ng "Positive-Unlabeled Learning for Disease Gene Identification" Bioinformatics, 2012.
[F] Peng Yang, Min Wu, Chee Keong Kwoh, Pavel P Khil, R Daniel Camerini-Otero, Teresa M Przytycka, Jie Zheng: "Predicting DNA Sequence Motifs of Recombination Hotspots by Integrative Visualization and Analysis" International Symposium on Integrative Bioinformatics (IB 2012).
[J] Peng Yang, Chee-Keong Kwoh, Jianping Mei: "Neighbor-Based Bipartite Learning Model for Small Molecule-Target Interaction Identification" Journal of Medical Imaging and Health Informatics, 2012
[F] Jian-Ping Mei, Chee-Keong Kwoh, Peng Yang, Xiao-Li Li, Jie Zheng "Globalized bipartite local model for drug-target interaction prediction" 11th International Workshop on Data Mining in Bioinformatics (BIOKDD'12)
2011
[J] Peng Yang, Xiaoli Li, Min Wu, Chee-Keong Kwoh, See-Kiong Ng "Inferring gene-phenotype associations via global protein complex network propagation" PloS one, 2011.