Weiyang Liu

 

Google Scholar   Github

 

University of Cambridge
Max Planck Institute for Intelligent Systems

About Me

I conduct research at Cambridge and MPI Tübingen with Adrian Weller and Bernhard Schölkopf. Previously, I spent wonderful years at Georgia Tech, working with Le Song and James Rehg. I have also spent time at Google Brain, Nvidia, and MERL.

 

My research interest broadly lies in Machine Learning. My research aims to tackle 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. See my favorite selection for a research overview. My research is/was generously supported by Leverhulme Trust, Cambridge-Tübingen Fellowship and Baidu Fellowship.

 

I believe that everything should be made as simple as possible, but not simpler.

Publications

Learning with Hyperspherical Uniformity
Weiyang Liu, Rongmei Lin, Zhen Liu, Li Xiong, Bernhard Schölkopf, Adrian Weller

AISTATS 2021

arXiv | code | bib

  @InProceedings{Liu2021HyperUni,
      title={Learning with Hyperspherical Uniformity},
      author={Liu, Weiyang and Lin, Rongmei and Liu, Zhen and Xiong, Li and Schölkopf, Bernhard and Weller, Adrian},
      booktitle={AISTATS},
      year={2021}}

Orthogonal Over-Parameterized Training
Weiyang Liu*, Rongmei Lin*, Zhen Liu, James Rehg, Liam Paull, Li Xiong, Le Song, Adrian Weller

CVPR 2021

arXiv | code | bib

  @InProceedings{Liu2021OPT,
      title={Orthogonal Over-Parameterized Training},
      author={Liu, Weiyang and Lin, Rongmei and Liu, Zhen and Rehg, James M. and Paull, Liam 
       and Xiong, Li and Song, Le and Weller, Adrian},
      booktitle={CVPR},
      year={2021}}

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

ICML 2020

arXiv | project | code | talk | long talk | slides | bib

  @InProceedings{Chen20AVH,
      title={Angular Visual Hardness},
      author={Chen, Beidi and Liu, Weiyang and Garg, Animesh and Yu, Zhiding 
       and Shrivastava, Anshumali and Anandkumar, Animashree},
      booktitle={ICML},
      year={2020}}

Regularizing Neural Networks via Minimizing Hyperspherical Energy
Rongmei Lin, Weiyang Liu*, Zhen Liu, Chen Feng, Zhiding Yu, James Rehg, Li Xiong, Le Song

CVPR 2020

arXiv | code | talk | slides | bib

  @InProceedings{Lin20CoMHE,
      title={Regularizing Neural Networks via Minimizing Hyperspherical Energy},
      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},
      booktitle={CVPR},
      year={2020}}

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

NeurIPS 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

NeurIPS 2019

arXiv | code | 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

NeurIPS 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={NeurIPS},
      year={2018}}

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

NeurIPS 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={NeurIPS},
      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}}

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

ICLR 2018   Workshop   Most Popular Paper

arXiv | code | openreview | journal | 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}}

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   Most Influential Paper

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}}
Last updated on 20th Aug. 2020.
This site has been visisted Free Web Counter times in total.