photo

Shan You 游山

Make it simple. Make it work.

I am currently a Senior Researcher at SenseTime Research working with Fei Wang and Chen Qian, and also a post doc at Tsinghua University supervised by Prof. Changshui Zhang (IEEE Fellow). Before that, I received my Ph.D. degree in computer science from the School of EECS, Peking University in 2019, advised by Prof. Chao Xu. I am also very hornored to be jointly supervised by Prof. Dacheng Tao (IEEE Fellow) when visiting the UBTech Sydney AI Institute, the University of Sydney. In 2014, I received my bachelor's degree both in mathematics and applied mathematics (elite class) and in English at Xi'an Jiaotong University.

  youshan@sensetime.com                               Google Scholar

Research Interest

My research interests include AutoML, reinforcement learning and other computer vision and machine learning topics, such as face recognition and object tracking.


Recruit

I'm recruiting self-motivated employees and interns who have strong coding skills and impressive research background to work with me on computer vision and AutoML related topics. Welcome to send me your detailed resume!


News

  • [2021/07] Three papers were accepted to ICCV 2021!
  • [2021/07] We released a new self-supervised learning paradigm ReSSL on Arxiv, which achieves new SOTA results. The code is available at Github.
  • [2021/07] I will serve as a member of the novel Program Committee Board (PCB) of IJCAI.
  • [2021/06] We released Vision Transformer Architecture Search on Arxiv, and the code is available at Github.
  • [2021/05] One paper about NAS was accepted to ICML 2021! We proposed a new K-shot weight sharing paradigm.
  • [2021/04] We are organizing a workshop about model mining on the KDD 2021. Submition details refer to the official webcite.
  • [2021/03] We have released a NAS Benchmark on the one-shot MobileNetV2 space. [Github]
  • [2021/03] Three papers about NAS were accepted to CVPR 2021!
  • [2021/01] One paper about channel number search was accepted to ICLR 2021 as Spotlight!
  • [2020/10] One paper about quantum NAS was released on Arxiv.
  • [2020/09] Two papers were accepted to NeurIPS 2020.
  • [2020/02] One paper about NAS was accepted to CVPR 2020.
  • [2019/05] In 7th Visual Object Tracking (VOT 2019) Challenge, our team won the 1st place in RT track. Check the report at ICCV 2019 workshop.

Publications

2021

Weakly Supervised Contrastive Learning
Mingkai Zheng, Shan You, Fei Wang, Chen Qian, Changshui Zhang, Xiaogang Wang, Chang Xu
International Conference on Computer Vision (ICCV), 2021
[PDF]

PDNAS: On the Predictability of Supernet for Shrinking Architecture Search Space
Lujun Li, Shan You, Fei Wang, Chen Qian, Changshui Zhang, Xiaogang Wang, Qingyi Gu
International Conference on Computer Vision (ICCV), 2021
[PDF]

Learning with Privileged Tasks
Yuru Song, Zan Lou, Shan You, Erkun Yang, Fei Wang, Chen Qian, Changshui Zhang, Xiaogang Wang
International Conference on Computer Vision (ICCV), 2021
[PDF]

K-shot NAS: Learnable Weight-Sharing for NAS with K-shot Supernets
Xiu Su*, Shan You*, Fei Wang, Chen Qian, Changshui Zhang, Chang Xu (*co-first author)
International Conference on Machine Learning (ICML), 2021
[PDF]

BCNet: Searching for Network Width with Bilaterally Coupled Network
Xiu Su, Shan You, Fei Wang, Chen Qian, Changshui Zhang, Chang Xu
The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021
[PDF]

Towards Improving the Consistency, Efficiency, and Flexibility of Differentiable Neural Architecture Search
Yibo Yang, Shan You, Hongyang Li, Fei Wang, Chen Qian, Zhouchen Lin
The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021
[Arxiv]

Prioritized Architecture Sampling with Monto-Carlo Tree Search
Xiu Su, Tao Huang, Yanxi Li, Shan You, Fei Wang, Chen Qian, Changshui Zhang, Chang Xu
The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021
[PDF] [Code for Benchmark]

Locally Free Weight Sharing for Network Width Search
Xiu Su, Shan You, Tao Huang, Fei Wang, Chen Qian, Changshui Zhang, Chang Xu
International Conference on Learning Representations (ICLR, Spotlight), 2021
[PDF]

2020

Agree to Disagree: Adaptive Ensemble Knowledge Distillation in Gradient Space
Shangchen Du*, Shan You*, Xiaojie Li, Jianlong Wu, Fei Wang, Chen Qian, Changshui Zhang (*co-first author)
Advances in Neural Information Processing Systems (NeurIPS), 2020
[PDF] [Code]

ISTA-NAS: Efficient and Consistent Neural Architecture Search by Sparse Coding
Yibo Yang, Hongyang Li, Shan You, Fei Wang, Chen Qian, Zhouchen Lin
Advances in Neural Information Processing Systems (NeurIPS), 2020
[PDF] [Code]

GreedyNAS: Towards Fast One-Shot NAS with Greedy Supernet
Shan You, Tao Huang, Mingmin Yang, Fei Wang, Chen Qian, Changshui Zhang
The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020
[PDF] [Poster] [Promotion Video]

Reborn Filters: Pruning Convolutional Neural Networks with Limited Data
Yehui Tang, Shan You, Chang Xu, Jin Han, Chen Qian, Boxin Shi, Chao Xu, Changshui Zhang
AAAI Conference on Artificial Intelligence (AAAI), 2020
[PDF]

Learning Student Networks with Few Data
Shumin Kong, Tianyu Guo, Shan You, Chang Xu
AAAI Conference on Artificial Intelligence (AAAI), 2020
[PDF]

2019

Reinforced Molecule Generation with Heterogeneous States
Fangzhou Shi, Shan You, Chang Xu
IEEE International Conference on Data Mining (ICDM, Oral), 2019
[PDF]

2018

Online Dictionary Learning with Confidence
Shan You, Chang Xu, Chao Xu
IEEE International Conference on Data Mining (ICDM, Oral), 2018
[PDF]

Learning with Single-Teacher Multi-Student
Shan You, Chang Xu, Chao Xu, Dacheng Tao
AAAI Conference on Artificial Intelligence (AAAI), 2018
[PDF]

2017

Learning from Multiple Teacher Networks
Shan You, Chang Xu, Chao Xu, Dacheng Tao
ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2017
[PDF] [Spotlight]

Privileged Multi-label Learning
Shan You, Chang Xu, Yunhe Wang, Chao Xu, Dacheng Tao
International Joint Conference on Artificial Intelligence (IJCAI), 2017
[PDF]

DCT Regularized Extreme Visual Recovery
Yunhe Wang, Chang Xu, Shan You, Chao Xu, Dacheng Tao
IEEE Transactions on Image Processing (TIP), 2017
[PDF]

Fast Compressive Phase Retrieval under Bounded Noise
Hongyang Zhang, Shan You, Zhouchen Lin, Chao Xu
AAAI Conference on Artificial Intelligence (AAAI), 2017
[PDF]

2016

CNNpack: Packing Convolutional Neural Networks in the Frequency Domain
Yunhe Wang, Chang Xu, Shan You, Chao Xu, Dacheng Tao
Neural Information Processing Systems (NIPS), 2016
[PDF] [Supp]

DCT inspired feature transform for image retrieval and reconstruction
Yunhe Wang, Miaojing Shi, Shan You, Chao Xu
IEEE Transactions on Image Processing (TIP), 2017
[PDF]


Manuscripts

ReSSL: Relational Self-Supervised Learning with Weak Augmentation
Mingkai Zheng, Shan You, Fei Wang, Chen Qian, Changshui Zhang, Xiaogang Wang, Chang Xu
[Arxiv]

Vision Transformer Architecture Search
Xiu Su, Shan You, Jiyang Xie, Mingkai Zheng, Fei Wang, Chen Qian, Changshui Zhang, Xiaogang Wang, Chang Xu
[Arxiv]

Explicitly Learning Topology for Differentiable Neural Architecture Search
Tao Huang, Shan You, Yibo Yang, Zhuozhuo Tu, Fei Wang, Chen Qian, Changshui Zhang
[Arxiv]

Data Agnostic Filter Gating for Efficient Deep Networks
Xiu Su, Shan You, Tao Huang, Hongyan Xu, Fei Wang, Chen Qian, Changshui Zhang, Chang Xu
[Arxiv]

Quantum circuit architecture search: error mitigation and trainability enhancement for variational quantum solvers
Yuxuan Du, Tao Huang, Shan You, Min-Hsiu Hsieh, Dacheng Tao
[Arxiv]

On the learnability of quantum neural networks
Yuxuan Du, Min-Hsiu Hsieh, Tongliang Liu, Shan You, Dacheng Tao
[Arxiv]

Quantum differentially private sparse regression learning
Yuxuan Du, Min-Hsiu Hsieh, Tongliang Liu, Shan You, Dacheng Tao
[Arxiv]

Bringing Giant Neural Networks Down to Earth with Unlabeled Data
Yehui Tang, Shan You, Chang Xu, Boxin Shi, Chao Xu
[Arxiv]

Streaming Label Learning for Modeling Labels on the Fly
Shan You, Chang Xu, Yunhe Wang, Chao Xu, Dacheng Tao
[Arxiv]


Academic Services

Reviewer for Conferences:
International Conference on Machine Learning (ICML, 2021/2020)
Neural Information Processing Systems (NeurIPS, 2021/2020/2018/2016)
International Conference on Learning Representations (ICLR, 2022/2021)
IEEE Conference on Computer Vision and Pattern Recognition (CVPR, 2022/2021)
International Conference on Computer Vision (ICCV, 2021)
AAAI Conference on Artificial Intelligence (AAAI, 2022/2021/2020/2019, PC member)
International Joint Conferences on Artificial Intelligence (IJCAI, 2021/2020/2019/2018/2017, (Senior) PC member)
ACM International Conference on Multimedia (ACMMM, 2021)

Reviewer for Journals:
IEEE Journal on Selected Areas on Communications (JSAC), Pattern Recognition (PR), Information Sciences, Neurocomputing

Volunteering:
International Conference on Machine Learning (ICML, 2017)
The 10th Joint workshop on Machine Perception and robotics (MPR, 2014)


Selected Awards

[2019/05] Champion of 7th Visual Object Tracking (VOT 2019) Challenge in RT track. Check the report at ICCV 2019 workshop.
[2019/06] Qualcomm Scholarship, Peking University
[2019/05] Outstanding Graduates of Beijing, Beijing
[2019/05] Outstanding Graduates of Peking University, Peking University
[2018/06] Presidential Scholarship of Peking University, Peking University