Weiyang Liu

 

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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

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

Tech Report (v3), 2020

arXiv | code | bib

  @article{Liu2020OPT,
      title={Orthogonal Over-Parameterized Training},
      author={Liu, Weiyang and Lin, Rongmei and Liu, Zhen and Rehg, James M. and Xiong, Li and Weller, Adrian and Song, Le},
      journal={arXiv preprint arXiv:2004.04690},
      year={2020}}

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

ICML 2020

arXiv | 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

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 | 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}}

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

ICLR 2018   Workshop   IEEE 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

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.
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