Yisen Wang


Yisen Wang 王奕森
PhD Candidate
Department of Computer Science and Technology
Tsinghua University, Beijing, China


Email: wangys14 AT mails DOT tsinghua.edu.cn
Homepage: https://www.cc.gatech.edu/~ywang3430/

[CV] [Google Scholar] [Github]



Biography

I am currently a visiting scholar at Georgia Tech, supervised by Prof. Hongyuan Zha and Prof. Le Song. I am a PhD Candidate in the Department of Computer Science and Technology, Tsinghua University, China, supervised by Prof. Shu-Tao Xia. At June 2016, I am lucky to visit School of Computing and Information Systems, The University of Melbourne, Australia, under the supervision of Prof. James Bailey.

My research interest broadly includes machine learning, deep learning and their theory and applications.

News


Publications  Google Scholar

-Journal Articles

  1. A Novel Consistent Random Forests Framework [PDF]
    Yisen Wang, Shu-Tao Xia, Qingtao Tang, Jia Wu, Xingquan Zhu
    IEEE Transactions on Neural Networks and Learning Systems (TNNLS, JCR: Q1, IF: 7.982), 2017.

  2. Link Sign Prediction by Variational Bayesian Probabilistic Matrix Factorization with Student-t Prior [PDF]
    Yisen Wang*, Fangbing Liu*, Shu-Tao Xia, Jia Wu
    Information Sciences(IS, JCR: Q1, IF: 4.832), Volume 405, September 2017, Pages 175 -- 189.

  3. A Less-greedy Two-term Tsallis Entropy Information Metric Approach for Decision Tree Classification [PDF]
    Yisen Wang, Shu-Tao Xia, Jia Wu
    Knowledge-Based Systems(KBS, JCR: Q1, IF: 4.529), Volume 120, March 2017, Pages 34 -- 42.

  4. End-to-end coding for TCP [PDF]
    Yong Cui, Lian Wang, Xin Wang, Yisen Wang, Fengyuan Ren, Shu-Tao Xia
    IEEE Network(IF: 7.230), Volume 30, Issue 2, 2016, Pages 68-73.

  5. Collaborative Representation Cascade for Single-Image Super-Resolution [PDF]
    Yongbing Zhang, Yulun Zhang, Jian Zhang, Dong Xu, Yun Fu, Yisen Wang, Xiangyang Ji, Qionghai Dai
    IEEE Transactions on Systems, Man, and Cybernetics: Systems(IF: 2.350), 2017.

  6. A generic denoising framework via guided principal component analysis [PDF]
    Tao Dai, Zhiya Xu, Haoyi Liang, Ke Gu, Qingtao Tang, Yisen Wang, Weizhi Lu, Shu-Tao Xia
    Journal of Visual Communication and Image Representation(IF: 2.164), 2017.


-Conference Papers

  1. Dimensionality-Driven Learning with Noisy Labels[PDF]
    Yisen Wang*, Xingjun Ma*, Michael Houle, Shu-Tao Xia, James Bailey
    International Conference on Machine Learning(ICML 2018), Stockholm, Sweden, 2018

  2. Iterative Learning with Open-set Noisy Labels [PDF]
    Yisen Wang, Weiyang Liu, Xingjun Ma, James Bailey, Hongyuan Zha, Le Song, Shu-Tao Xia
    Computer Vision and Pattern Recognition (CVPR 2018), Salt Lake City, USA, 2018 (Spotlight)

  3. Decoupled Networks [PDF][Appendix]
    Weiyang Liu, Zhen Liu, Zhiding Yu, Bo Dai, Yisen Wang, James Rehg, Le Song
    Computer Vision and Pattern Recognition (CVPR 2018), Salt Lake City, USA, 2018 (Spotlight)

  4. Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality [PDF] [Code]
    Xingjun Ma*, Bo Li*, Yisen Wang*, Sarah M. Erfani, Sudanthi Wijewickrema, Michael E. Houle, Grant Schoenebeck, Dawn Song, James Bailey
    6th International Conference on Learning Representations (ICLR 2018), Vancouver, BC, Canada, 2018 (Oral (2%))

  5. Residual convolutional CTC networks for automatic speech recognition [PDF]
    Yisen Wang*, Xuejiao Deng*, Songpai Pu, Zhiheng Huang, Dan Su, Shu-Tao Xia
    Preprint Arxiv, 2017

  6. Unbiased Multivariate Correlation Analysis [PDF]
    Yisen Wang, Simone Romano, Nguyen Vinh, James Bailey, Xingjun Ma, Shu-Tao Xia
    Thirty-First AAAI Conference on Artificial Intelligence (AAAI 2017), San Francisco, California, USA, 2017. (Oral)

  7. Unifying Attribute Splitting Criteria of Decision Trees by Tsallis Entropy [PDF]
    Yisen Wang, Shu-Tao Xia
    42nd IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2017), New Orleans, Louisiana, USA, 2017. (Poster)

  8. Student-t Process Regression with Student-t Likelihood [PDF]
    Qingtao Tang, Li Niu, Yisen Wang, Tao Dai, Wangpeng An, Jianfei Cai, Shu-Tao Xia
    Twenty-sixth International Joint Conference on Artificial Intelligence (IJCAI 2017), Melbourne, Australia, 2017. (Oral)

  9. Robust Survey Aggregation with Student-t Distribution and Sparse Representation [PDF]
    Qingtao Tang, Tao Dai, Li Niu, Yisen Wang, Shu-Tao Xia, Jianfei Cai
    Twenty-sixth International Joint Conference on Artificial Intelligence (IJCAI 2017), Melbourne, Australia, 2017. (Oral)

  10. Bernoulli Random Forests: Closing the Gap between Theoretical Consistency and Empirical Soundness [PDF]
    Yisen Wang, Qingtao Tang, Shu-Tao Xia, Jia Wu, Xingquan Zhu
    Twenty-fifth International Joint Conference on Artificial Intelligence (IJCAI 2016), New York, New York, USA, 2016. (Oral)

  11. Improving Decision Trees by Tsallis Entropy Information Metric Method [PDF]
    Yisen Wang, Chaobing Song, Shu-Tao Xia
    International Joint Conference on Neural Networks (IJCNN 2016), Vancouver, British Columbia, Canada, 2016. (Oral)

  12. A Novel Feature Subspace Selection Method in Random Forests for High Dimensional Data [PDF]
    Yisen Wang, Shu-Tao Xia
    International Joint Conference on Neural Networks (IJCNN 2016), Vancouver, British Columbia, Canada, 2016. (Oral)

  13. Student-t Process Regression with Dependent Student-t Noise [PDF]
    Qingtao Tang, Yisen Wang, Shu-Tao Xia
    European Conference on Artificial Intelligence (ECAI 2016), Hague, Netherlands, 2016. (Oral)


Professional Activities

-Reviewers

Awards


Last update : 2/21/2018