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Ying WEI (魏 颖)
yingwei [at] cityu [dot] edu [dot] hk

I am currently an Assistant Professor with Department of Computer Science, City University of Hong Kong.

I am interested in developing algorithms that equip machines with more general intelligence via knowledge transfer. This includes representing and structuring the knowledge from previous tasks, allowing machines to transfer and apply the knowledge to quickly learn the current task with minimal human supervision, and autonomously evaluating the success of knowledge transfer.

Previously, I was a senior researcher at Tencent AI Lab. I completed my Ph.D. in Computer Science and Engineering at Hong Kong University of Science and Technology under the supervision of Professor Qiang Yang, and my B.S. in Automation at Huazhong University of Science and Technology. I have also spent time interning at Microsoft Research Asia.

I am looking for highly-motivated full-time and joint programme PhD students! Postdoc positions are also available.

PhD Thesis  /  LinkedIn  /  Google Scholar

News
  • Serving as a senior program committee member for AAAI 2021
  • Serving as a program committee member for NeurIPS 2021
  • [May 2021] Our paper "Improving Generalization in Meta-learning via Task Augmentation" was accepted by ICML 2021
  • [May 2021] Our paper "Meta-learning Hyperparameter Performance Prediction with Neural Processes" was accepted by ICML 2021
  • [Feb 2021] I joined City University of Hong Kong as an Assistant Professor
  • Serving as a program committee member for ICML 2021
  • Serving as a senior program committee member for AAAI 2021
  • Serving as a program committee member for ICLR 2021
  • Serving as a program committee member for WWW 2021
  • Our paper "Learn to Cross-lingual Transfer with Meta Graph Learning Across Heterogeneous Languages" was accepted by EMNLP 2020
  • Our paper "Self-Supervised Graph Transformer on Large-Scale Molecular Data" was accepted by NeurIPS 2020
  • Our paper "Adversarial Sparse Transformer for Time Series Forecasting" was accepted by NeurIPS 2020
  • Our paper "Collaborative Unsupervised Domain Adaptation for Medical Image Diagnosis" was accepted by IEEE Transactions on Image Processing
  • Our paper "TranSlider: Transfer Ensemble Learning from Exploitation to Exploration" was accepted by KDD 2020
  • Serving as a program committee member for ECML/PKDD 2020
  • Serving as a program committee member for NeurIPS 2020
  • Serving as a program committee member for ICML 2020
  • Our paper "Graph Few-shot Learning via Knowledge Transfer" was accepted by AAAI 2020
  • Serving as a program committee member for IJCAI 2020
  • Serving as a program committee member for WWW 2020
  • Our paper "Transferable Neural Processes for Hyperparameter Optimization" was accepted by the Meta Learning workshop at NeurIPS 2019
  • Our paper "Graph Few-shot Learning via Knowledge Transfer" was accepted by the Graph Representation Learning workshop at NeurIPS 2019
  • Serving as a reviewer for ICLR 2020
  • Recognized as one of the highest-scoring reviewers for NeurIPS 2019
  • Serving as a senior program committee member for AAAI 2020
  • Invited to be a session chair for IJCAI 2019
  • Our paper "Hierarchically-structured Meta-learning" was accepted by ICML 2019
Publications


( ___: equal contribution, *: corresponding author)

Meta-learning Hyperparameter Performance Prediction with Neural Processes
Ying Wei, Peilin Zhao, Junzhou Huang,
38th International Conference on Machine Learning (ICML), 2021
pdf / code

Improving Generalization in Meta-learning via Task Augmentation
Huaxiu Yao, Long-Kai Huang, Linjun Zhang, Ying Wei*, Li Tian, James Zou, Junzhou Huang, Zhenhui Li
38th International Conference on Machine Learning (ICML), 2021
pdf / arXiv / code

Learn to Cross-lingual Transfer with Meta Graph Learning Across Heterogeneous Languages
Zheng Li, Mukul Kumar, William Headden, Bing Yin, Ying Wei, Yu Zhang, Qiang Yang
2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2020
pdf

Self-Supervised Graph Transformer on Large-Scale Molecular Data
Yu Rong, Yatao Bian, Tingyang Xu, Weiyang Xie, Ying Wei, Wenbing Huang, Junzhou Huang
34th Annual Conference on Neural Information Processing Systems (NeurIPS), 2020
pdf

Adversarial Sparse Transformer for Time Series Forecasting
Sifan Wu, Xi Xiao, Qianggang Ding, Peilin Zhao, Ying Wei, Junzhou Huang
34th Annual Conference on Neural Information Processing Systems (NeurIPS), 2020
pdf

Collaborative Unsupervised Domain Adaptation for Medical Image Diagnosis
Yifan Zhang, Ying Wei, Qingyao Wu, Peilin Zhao, Shuaicheng Niu, Mingkui Tan, Junzhou Huang
IEEE Transactions on Image Processing, 2020
pdf

TranSlider: Transfer Ensemble Learning from Exploitation to Exploration
Kuo Zhong, Ying Wei*, Chun Yuan, Haoli Bai, Junzhou Huang
Twenty-sixth ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2020
pdf

Graph Few-shot Learning via Knowledge Transfer
Huaxiu Yao, Chuxu Zhang, Ying Wei*, Meng Jiang, Suhang Wang, Junzhou Huang, Nitesh Chawla, Zhenhui Li
Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI), 2020
pdf


Transferable End-to-End Aspect-based Sentiment Analysis with Selective Adversarial Learning
Zheng Li, Xin Li, Ying Wei, Lidong Bing, Yu Zhang, Qiang Yang
2019 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2019
pdf / code

From Whole Slide Imaging to Microscopy: Deep Microscopy Adaptation Network for Histopathology Cancer Image Classification
Yifan Zhang, Hanbo Chen, Ying Wei, Peilin Zhao, Jiezhang Cao, Xinjuan Fan, Xiaoying Lou, Hailing Liu, Jinlong Hou, Xiao Han, Jianhua Yao, Qingyao Wu, Mingkui Tan, Junzhou Huang
22nd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2019
pdf

Hierarchically Structured Meta-learning
Huaxiu Yao, Ying Wei*, Junzhou Huang, Zhenhui Li
36th International Conference on Machine Learning (ICML), 2019
pdf / code


Exploiting Coarse-to-Fine Task Transfer for Aspect-Level Sentiment Classification
Zheng Li, Ying Wei, Yu Zhang, Xiang Zhang, Xin Li
33rd AAAI Conference on Artificial Intelligence (AAAI) , 2019
pdf / code

Learning to Multitask
Yu Zhang, Ying Wei, Qiang Yang
32nd Annual Conference on Neural Information Processing Systems (NeurIPS), 2018
pdf

Transfer learning via Learning to Transfer
Ying Wei, Yu Zhang, Junzhou Huang, Qiang Yang
35th International Conference on Machine Learning (ICML), 2018
pdf

Hierarchical Attention Transfer Network for Cross-domain Sentiment Classification
Zheng Li, Ying Wei, Yu Zhang, Qiang Yang
32nd AAAI Conference on Artificial Intelligence (AAAI), 2018
pdf / code

Transferable Contextual Bandit for Cross-Domain Recommendation
Bo Liu, Ying Wei, Yu Zhang, Qiang Yang
32nd AAAI Conference on Artificial Intelligence (AAAI), 2018
pdf


End-to-End Adversarial Memory Network for Cross-domain Sentiment Classification
Zheng Li, Yu Zhang, Ying Wei, Qiang Yang
26th International Joint Conference on Artificial Intelligence (IJCAI), 2017
pdf / code

Deep Neural Networks for High Dimension, Low Sample Size Data
Bo Liu, Ying Wei, Yu Zhang, Qiang Yang
26th International Joint Conference on Artificial Intelligence (IJCAI), 2017
pdf

Heterogeneous Translated Hashing: A Scalable Solution towards Multi-modal Similarity Search
Ying Wei, Yangqiu Song, Yi Zhen, Bo Liu, Qiang Yang
ACM Transactions on Knowledge Discovery from Data (TKDD), 10(4):36, 2016
pdf

Transfer Knowledge between Cities
Ying Wei, Yu Zheng, Qiang Yang
22nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2016
pdf

Instilling Social to Physical: Co-Regularized Heterogeneous Transfer Learning
Ying Wei, Yin Zhu, Cane Wing-ki Leung Yangqiu Song, Qiang Yang
30th AAAI Conference on Artificial Intelligence (AAAI), 2016
pdf

Scalable Heterogeneous Translated Hashing
Ying Wei, Yangqiu Song, Yi Zhen, Bo Liu, Qiang Yang
20th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2014
Best Paper Finalist
pdf



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