Ying WEI (魏 颖)
judyweiying at gmail dot com

I am currently a senior researcher at Tencent AI Lab.

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 completed my Ph.D. in Computer Science and Engineering at Hong Kong University of Science and Technology and my B.S. in Automation at Huazhong University of Science and Technology. I have also spent time interning at Microsoft Research Asia.

CV  /  PhD Thesis  /  LinkedIn

News
  • Serving as a program committe member for ICML 2020
  • Our paper "Graph Few-shot Learning via Knowledge Transfer" is accepted by AAAI 2020
  • Serving as a program committe member for WWW 2020
  • Our paper "Transferable Neural Processes for Hyperparameter Optimization" is accepted by the Meta Learning workshop at NeurIPS 2019
  • Our paper "Graph Few-shot Learning via Knowledge Transfer" is accepted by the Graph Representation Learning workshop at NeurIPS 2019
  • Our paper "Collaborative Unsupervised Domain Adaptation for Medical Image Diagnosis" is accepted by the Medical Imaging meets NeurIPS 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" is accepted by ICML 2019
Publications

(*: equal contribution, ___: intern that I have mentored)

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 / code


Collaborative Unsupervised Domain Adaptation for Medical Image Diagnosis
Yifan Zhang, Ying Wei, Peilin Zhao, Shuaicheng Niu, Qingyao Wu, Mingkui Tan, Junzhou Huang
The Medical Imaging Meets NeurIPS Workshop at NeurIPS, 2019

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


The source code of this website is adapted from both this and this page.