Publication

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.

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