|
M.Sc. Student @ IIP Group Email: weisun_@outlook.com | |
Supervisor
- Professor Jun-Yuan Xie
Biography
- I received my B.Sc. degree in of Soochow University in June 2017. In the same year, I was admitted to study for a Master degree in Nanjing University without entrance examination. Currently I am a second year M.Sc. student of Department of Computer Science and Technology in Nanjing University and a member of IIP Group, led by professor Jun-Yuan Xie and Chong-Jun Wang.
Research Interest
Machine Learning & Multi-label Learning.
- On Multi-label Text Classification (MLTC), text features can be regarded as detailed description of documents and label sets can be a summarization of documents. Hybrid Topics from text features and label sets by LDA (a method of topic model) can effectively mine global label correlations and deeper features. Meanwhile, a pair including topics and labels can mitigate the imbalanced problem of labels.
- Deep learning For multi-label text classification. We utilize dilated convolution to obtain the semantic understanding of the text and design a hybrid attention mechansim for different labels (Specifically, each label should attend to most relevant textual contents). Firstly, we initialize trainable label embeddings. Then After obationing word-level information based on Bi-LSTM, we get semantic understanding of texts based on word-level information by dilated convolution. Finally, we design a hybrid attention for different labels based on label embeddings. Besides, we add label cooccurrence matrix into loss function to guide the whole network to learn and achieve good results.
- GCN (Graph Convolution Network) can be used to exploit more complex label correlations on Image Multi-label Learning.
Publications
- Ran X., Pan Y., Sun W. and Wang C.. Learn to Select via Hierarchical Gate Mechanism for Aspect-Based Sentiment Analysis. In Proceedings of IJCAL 2019.
- Sun W., Wang C..Multi-label Classification: Select Distinct Semantic Understanding for Different Labels[C]. In Proceedings of ApWeb-WAIM 2019.
- Sun W., Ran X.. Luo X., and Wang C..An Efficient Framework by Topic Model for Multi-label Text Classification. In Proceedings of IJCNN 2019.
- Xu Y., Ran X.. Sun W., Luo X. and Wang C..Gated Neural Network with Regularized Loss for Multi-label Text Classification. In Proceedings of IJCNN 2019.
- Ran X., Pan Y., Sun W. and Wang C.. Modeling More Globally: A Hierarchical Attention Network via Multi-Task Learning for Aspect-Based Sentiment Analysis. In Proceedings of DASFAA 2019, Chiang Mai, Thailand, Apr. 22-25, 2019: 505-509.
Resources
- Extreme Classification Repository: for large-scale multi-label datasets and off-the-shelf eXtreme Multi-Label Learning (XML) solvers.
- Mulan Multi-Label Learning Datasets: regular/traditional multi-label learning datasets.
- Related Work: This page categorizes a list of works of my interest, mainly in Multi-Label Learning.
Rewards or Honors
- Second-Class Academic Scholarship, 2018-2019
- First-Class Academic Scholarship, 2017-2018
- Outstanding Graduate Student, 2017.06
- CCF Excellent University Student, 2016.10
- National Scholarship, 2015.11