Weiyang Liu

 

Google Scholar   Github

 

College of Computing
Georgia Institute of Technology

About Me

I am conducting research at Georgia Tech with Prof. Le Song and Prof. James Rehg. I have also spent time at Google Brain, Nvidia Research, and MERL as a research intern.

 

My research interest broadly lies in Machine Learning and Perception. My research aims to tackle challenging fundamental yet practical problems, and develop "light-and-sweet" algorithms: (i) light: conceptually simple in methodology and easy to implement in practice, (ii) sweet: having clear intuitions and non-trivial theoretical guarantees. I believe that everything should be made as simple as possible, but not simpler.

 

My previous research mainly focuses on Hyperspherical Learning. I am particularly interested in and pay most attention to research topics including Geometric Learning, Meta Learning, Interactive Machine Learning, and Multi-Modal Perception.

Publications

Neural Similarity Learning
Weiyang Liu, Zhen Liu, James Rehg, Le Song

NIPS 2019

arXiv | code | talk | slides | bib

  @InProceedings{LiuNIPS19,
      title={Neural Similarity Learning},
      author={Liu, Weiyang and Liu, Zhen and Rehg, James and Song, Le},
      booktitle={NeurIPS},
      year={2019}}

Meta Architecture Search
Albert Shaw, Wei Wei, Weiyang Liu, Le Song, Bo Dai

NIPS 2019

arXiv | code | workshop | poster | bib

  @InProceedings{ShawNIPS19,
      title={Meta Architecture Search},
      author={Shaw, Albert and Wei, Wei and Liu, Weiyang and Song, Le and Dai, Bo},
      booktitle={NeurIPS},
      year={2019}}

Disjoint Mapping Network for Cross-modal Matching of Voices and Faces
Yandong Wen, Mahmoud Alismail, Weiyang Liu, Bhiksha Raj, Rita Singh

ICLR 2019

arXiv | code | openreview | poster | bib

  @InProceedings{Wen2019DIM,
      title={Disjoint Mapping Network for Cross-modal Matching of Voices and Faces},
      author={Wen, Yandong and Alismail, Mahmoud and Liu, Weiyang and Raj, Bhiksha and Singh, Rita},
      booktitle={ICLR},
      year={2019}}

Learning towards Minimum Hyperspherical Energy
Weiyang Liu*, Rongmei Lin*, Zhen Liu*, Lixin Liu*, Zhiding Yu, Bo Dai, Le Song

NIPS 2018

arXiv | code | project | sphereface+ | talk | slides | bib

  @InProceedings{LiuNIPS18,
      title={Learning towards Minimum Hyperspherical Energy},
      author={Liu, Weiyang and Lin, Rongmei and Liu, Zhen and Liu, Lixin and Yu, Zhiding and Dai, Bo and Song, Le},
      booktitle={NIPS},
      year={2018}}

Coupled Variational Bayes via Optimization Embedding
Bo Dai, Hanjun Dai, Niao He, Weiyang Liu, Zhen Liu, Jianshu Chen, Lin Xiao, Le Song

NIPS 2018

arXiv | code | poster | bib

  @InProceedings{DaiNIPS18,
      title={Coupled Variational Bayes via Optimization Embedding},
      author={Dai, Bo and Dai, Hanjun and He, Niao and Liu, Weiyang 
       and Liu, Zhen and Chen, Jianshu and Xiao, Lin and Song, Le},
      booktitle={NIPS},
      year={2018}}

Simultaneous Edge Alignment and Learning
Zhiding Yu, Weiyang Liu, Yang Zou, Chen Feng, Srikumar Ramalingam, Vijaya Kumar, Jan Kautz

ECCV 2018

arXiv | code | project | demo | slides | bib

  @article{YuECCV18,
      title={Simultaneous Edge Alignment and Learning},
      author={Yu, Zhiding and Liu, Weiyang and Zou, Yang and Feng, Chen
       and Ramalingam, Srikumar and Kumar, Vijaya and Kautz, Jan},
      journal={arXiv preprint arXiv:1807.04836},
      year={2018}}

Towards Black-box Iterative Machine Teaching
Weiyang Liu, Bo Dai, Xingguo Li, Zhen Liu, James Rehg, Le Song

ICML 2018    

arXiv | talk | slides | bib

  @InProceedings{Liu2018ICML,
      author={Liu, Weiyang and Dai, Bo and Li, Xingguo and Rehg, James M and Song, Le},
      title = {Towards Black-box Iterative Machine Teaching},
      booktitle = {ICML},
      year = {2018}}

Decoupled Networks
Weiyang Liu*, Zhen Liu*, Zhiding Yu, Bo Dai, Rongmei Lin, Yisen Wang, James Rehg, Le Song

CVPR 2018   Spotlight

arXiv | code | talk | slides | bib

  @InProceedings{Liu2018DCNets,
      author = {Liu, Weiyang and Liu, Zhen and Yu, Zhiding and Dai, Bo and Lin, Rongmei
       and Wang, Yisen and Rehg, James M. and Song, Le},
      title = {Decoupled Networks},
      booktitle = {CVPR},
      year = {2018}}

Iterative Learning with Open-set Noisy Labels
Yisen Wang, Weiyang Liu, Xingjun Ma, James Bailey, Hongyuan Zha, Le Song, Shu-Tao Xia

CVPR 2018   Spotlight

arXiv | code | slides | bib

  @InProceedings{Wang2018ONL,
      author={Wang, Yisen and Liu, Weiyang and Ma, Xingjun and Bailey, James
       and Zha, Hongyuan and Song, Le and Xia, Shu-Tao},
      title={Iterative Learning with Open-set Noisy Labels},
      booktitle = {CVPR},
      year = {2018}}

Deep Hyperspherical Learning
Weiyang Liu, Yan-Ming Zhang, Xingguo Li, Zhiding Yu, Bo Dai, Tuo Zhao, Le Song

NIPS 2017   Spotlight

arXiv | code | project | talk | slides | bib

  @inproceedings{Liu2017NIPS,
      title={Deep Hyperspherical Learning},
      author={Liu, Weiyang and Zhang, Yan-Ming and Li, Xingguo and Yu, Zhiding and Dai, Bo and Zhao, Tuo and Song, Le},
      booktitle={NIPS},
      year={2017}}

Iterative Machine Teaching
Weiyang Liu, Bo Dai, Ahmad Humayun, Charlene Tay, Yu Chen, Linda Smith, James Rehg, Le Song

ICML 2017

arXiv | code | demo | talk | slides | bib

  @inproceedings{Liu2017ICML,
      title={Iterative Machine Teaching},
      author={Liu, Weiyang and Dai, Bo and Humayun, Ahmad and Tay, Charlene and Yu, Chen
       and Smith, Linda B and Rehg, James M and Song, Le},
      booktitle={ICML},
      year={2017}}

SphereFace: Deep Hypersphere Embedding for Face Recognition
Weiyang Liu, Yandong Wen, Zhiding Yu, Ming Li, Bhiksha Raj, Le Song
CVPR 2017

arXiv | code | project | demo | slides | bib

  @InProceedings{Liu2017CVPR,
      title = {SphereFace: Deep Hypersphere Embedding for Face Recognition},
      author = {Liu, Weiyang and Wen, Yandong and Yu, Zhiding and Li, Ming and Raj, Bhiksha and Song, Le},
      booktitle = {CVPR},
      year = {2017}}

Large-Margin Softmax Loss for Convolutional Neural Networks
Weiyang Liu, Yandong Wen, Zhiding Yu, Meng Yang
ICML 2016

arXiv | code | project | talk | slides | bib

  @inproceedings{Liu2016ICML,
      title={Large-Margin Softmax Loss for Convolutional Neural Networks},
      author={Liu, Weiyang and Wen, Yandong and Yu, Zhiding and Yang, Meng},
      booktitle={ICML},
      year={2016}}

Preprints / Workshops

Fast Iterative Machine Teaching
Zhaozhuo Xu, Beidi Chen, Weiyang Liu, Le Song, Anshumali Shrivastava

Technical Report, 2019

arXiv | code | slides | bib

  @article{Xu2019FIMT,
      title={Fast Iterative Machine Teaching via Locality Sensitive Sampling},
      author={Xu, Zhaozhuo and Chen, Beidi and Liu, Weiyang and Song, Le and Shrivastava, Anshumali}
      journal={Technical Report},
      year={2019}}

Angular Visual Hardness
Beidi Chen, Weiyang Liu, Animesh Garg, Zhiding Yu, Anshumali Shrivastava, Animashree Anandkumar

ICML 2019 Workshop on Deep Learning Phenomena   Oral

arXiv | code | talk | slides | bib

  @article{Chen2019AVH,
      title={Angular Visual Hardness},
      author={Chen, Beidi and Liu, Weiyang and Garg, Animesh and Yu, Zhiding 
       and Shrivastava, Anshumali and Anandkumar, Animashree},
      journal={ICML Workshop},
      year={2019}}

Compressive Hyperspherical Energy Minimization
Rongmei Lin*, Weiyang Liu*, Zhen Liu, Chen Feng, Zhiding Yu, James Rehg, Li Xiong, Le Song

Technical Report, 2019

arXiv | code | bib

  @article{LinCoMHE19,
      title={Compressive Hyperspherical Energy Minimization},
      author={Lin, Rongmei and Liu, Weiyang and Liu, Zhen and Feng, Chen and Yu, Zhiding 
       and Rehg, James M. and Xiong, Li and Song, Le},
      journal={arXiv preprint arXiv:1906.04892},
      year={2019}}

Additive Margin Softmax for Face Verification
Feng Wang, Weiyang Liu, Haijun Liu, Jian Cheng

ICLR 2018 Workshop    

arXiv | code | openreview | bib

  @article{Wang2018ICLRW,
      title = {Additive Margin Softmax for Face Verification},
      author = {Wang, Feng and Liu, Weiyang and Liu, Haijun and Cheng, Jian},
      journal = {arXiv preprint arXiv:1801.05599},
      year = {2018}}

Academic Service

  • Journal Reviewer: Nature Machine Intelligence, TPAMI, IJCV, TIP, etc.
  • Conference Reviewer: ICML, NIPS, ICLR, CVPR, ICCV, etc.

Awards

    • 2018    Baidu Scholarship
    • 2016    PKU Best Master Thesis
    • 2016    Beijing Outstanding Graduate Award
  • 2015    PKU Academic Innovation Award
  • 2013    SCUT Best Bachelor Thesis
    • 2012    National Scholarship (Three Times)
    • 2011    Hitachi Fellowship
    • 2011    Outstanding Winner in Mathematical Contest in Modeling (MCM/ICM)
Last updated on 4th Oct. 2019.
This site has been visisted Free Web Counter times in total.