Shuo Chen (陈 硕)

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Education & Experience
Honors and Awards
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Professional Activities

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Shuo Chen

Shuo Chen, D.Eng.

Research Scientist (≈Assistant Professor)

Center for Advanced Intelligence Project (AIP), RIKEN National Science Institute (理研), Japan.

[Google Scholar, DBLP]

E-mail: shuo.chen.ya@{foxmail.com, riken.jp}

Research Interests

  • Similairty Learning

  • Self-Supervised Learning

  • Representation Learning

  • Sparse and Low-Rank Theory

News

  • Mar. 2024: I will serve as an Area Chair for NeurIPS 2024.

  • Feb. 2024: One paper has been accepted by CVPR 2024.

  • Feb. 2024: I will serve as an Area Chair for ECCV 2024.

  • Jan. 2024: One paper has been accepted by ICLR 2024.

  • Dec. 2023: I will serve as an Area Chair for ICML 2024.

  • Nov. 2023: I serve as the Program Chair for International Workshop on Weakly Supervised Learning 2023.

  • Sep. 2023: Two papers have been accepted by NeurIPS 2023 and Machine Learning Journal.

  • Aug. 2023: I will serve as an Area Chair for ICLR 2024.

  • Jul. 2023: Two papers have been accepted by ICCV 2023.

  • May. 2023: Two papers have been accepted by ICML 2023 and Pattern Recognition.

  • Apr. 2023: I will serve as an Area Chair for NeurIPS 2023.

  • Mar. 2023: I received the Japanese RIKEN BAIHO Award and the Excellent Doctoral Dissertation Award of Chinese Institute of Electronics.

Education & Experience

  • Research Scientist (≈Assistant Professor [Ref1,Ref2,Ref3]), October 2023 -- Present
    Center for Advanced Intelligence Project, RIKEN National Science Institute, Japan.

  • Postdoc, August 2020 -- September 2023
    Center for Advanced Intelligence Project, RIKEN National Science Institute, Japan.

  • Visiting Ph.D., November 2018 -- June 2019
    Data Science Lab, The University of Pittsburgh, USA.

  • Algorithm Researcher, August 2015 -- November 2015
    SenseTime (Beijing Department), China.

  • Ph.D. (D.Eng.), September 2014 -- July 2020
    PCA-Lab, Nanjing University of Science and Technology (NJUST), China.

Honors and Awards

  • Excellent Doctoral Dissertation Award, Chinese Institute of Electronics (CIE), China, 2023.

  • RIKEN BAIHO Award (a.k.a. RIKEN Excellent Achievement Award, Annual Selection Rate < 1%), RIKEN National Science Institute, Japan, 2022.

  • Excellent Doctoral Dissertation Nomination, Chinese Association for Artificial Intelligence (CAAI), China, 2021.

  • Excellent Doctoral Dissertation Award (Annual Selection Rate < 2%), Jiangsu Education Department, China, 2021.

  • National Scholarship (Two Times, Annual Selection Rate < 2%), Ministry of Education, China, 2018 and 2019.

  • Top 1% GPA Ranking, School of Computer Science & Engineering, NJUST, China, 2014 -- 2019.

  • The 17th Mathematical Modeling Contest for Chinese Graduate Students, Honorable Mention, Ministry of Education, China, 2015.

  • The 2nd China Fuzzy Image Processing Contest,Honorable Mention, National Natural Science Foundation, China, 2015.

  • The 34th Mathematical Modeling Contest for American College Students, Honorable Mention, SIAM, USA, 2013.

  • The 2nd Software Programming Contest for Chinese College Students, Meritorious Winner, Ministry of Industry and Information Technology, China, 2012.

Highly Selected Publications

Conference Papers (* indicates corresponding authors)

  1. Efficiency Calibration of Implicit Regularization in Deep Networks via Self-Paced Curriculum-Driven Singular Value Selection.
    Zhe Li, Shuo Chen, Jian Yang, Lei Luo.
    International Joint Conference on Artificial Intelligence (IJCAI), 2024.

  2. Robust Similarity Learning with Difference Alignment Regularization.
    Shuo Chen, Gang Niu, Chen Gong, Okan Koc, Jian Yang, Masashi Sugiyama.
    International Conference on Learning Representations (ICLR), 2024.

  3. Self-Weighted Contrastive Learning among Multiple Views for Mitigating Representation Degeneration.
    Jie Xu, Shuo Chen, Yazhou Ren, Xiaoshuang Shi, Heng Tao Shen, Gang Niu, Xiaofeng Zhu.
    Neural Information Processing Systems (NeurIPS), 2023.

  4. Creative Birds: Self-Supervised Single-View 3D Style Transfer.
    Renke Wang (co-first), Guimin Que (co-first), Shuo Chen*, Xiang Li, Jun Li*, Jian Yang.
    International Conference on Computer Vision (ICCV), 2023.

  5. Distribution Shift Matters for Knowledge Distillation with Webly Collected Images.
    Jialiang Tang, Shuo Chen*, Gang Niu, Masashi Sugiyama, Chen Gong*.
    International Conference on Computer Vision (ICCV), 2023.

  6. Distortion and Uncertainty Aware Loss for Panoramic Depth Completion.
    Zhiqiang Yan, Xiang Li, Kun Wang, Shuo Chen*, Jun Li, Jian Yang*.
    International Conference on Machine Learning (ICML), 2023.

  7. Learning Contrastive Embedding in Low-Dimensional Space.
    Shuo Chen, Chen Gong, Jun Li, Jian Yang, Gang Niu, Masashi Sugiyama.
    Neural Information Processing Systems (NeurIPS), 2022.

  8. Linearity-Aware Subspace Clustering.
    Yesong Xu, Shuo Chen*, Jun Li, Jianjun Qian.
    AAAI Conference on Artificial Intelligence (AAAI), 2022, oral.

  9. Industrial Style Transfer with Large-scale Geometric Warping and Content Preservation.
    Jinchao Yang (co-first), Fei Guo (co-first), Shuo Chen, Jun Li, Jian Yang.
    IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2022

  10. Large-Margin Contrastive Learning with Distance Polarization Regularizer.
    Shuo Chen, Gang Niu, Chen Gong, Jun Li, Jian Yang, Masashi Sugiyama.
    International Conference on Machine Learning (ICML), 2021

  11. Understanding the Disharmony between Weight Normalization Family and Weight Decay.
    Xiang Li, Shuo Chen, Jian Yang.
    AAAI Conference on Artificial Intelligence (AAAI), 2020.

  12. Curvilinear Distance Metric Learning.
    Shuo Chen, Lei Luo, Jian Yang, Chen Gong, Jun Li, Heng Huang.
    Neural Information Processing Systems (NeurIPS), 2019.

  13. Understanding the Disharmony between Dropout and Batch Normalization by Variance Shift.
    Xiang Li, Shuo Chen, Xiaolin Hu, Jian Yang.
    IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2019.

  14. Data-Adaptive Metric Learning with Scale Alignment.
    Shuo Chen, Chen Gong, Jian Yang, Ying Tai, Jun Li.
    AAAI Conference on Artificial Intelligence (AAAI), 2019.

  15. Adversarial Metric Learning.
    Shuo Chen, Chen Gong, Jian Yang.
    International Joint Conference on Artificial Intelligence (IJCAI), 2018.

Journal Papers (* indicates corresponding authors)

  1. Boosting Graph Contrastive Learning via Adaptive Sampling.
    Sheng Wan, Yibing Zhan, Shuo Chen, Shirui Pan, Jian Yang, Dacheng Tao, Chen Gong.
    IEEE Transactions on Neural Network and Learning System (T-NNLS), 2023.

  2. Similarity-Agnostic Contrastive Learning with Alternative Self-Supervision.
    Shuo Chen, Gang Niu, Chen Gong, Jun Li, Jian Yang, Masashi Sugiyama.
    IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), in peer review.

  3. Fast Subspace Clustering by Learning Projective Block Diagonal Representation.
    Yesong Xu, Shuo Chen*, Chunyan Xu. Jun Li*, Zongyan Han, Jian Yang.
    Pattern Recognition (PR), 2023.

  4. Boundary-Restricted Metric Learning.
    Shuo Chen, Chen Gong, Xiang Li, Jian Yang, Gang Niu, Masashi Sugiyama.
    Machine Learning Journal (MLJ), 2023.

  5. Streaming Feature Selection via Graph Diffusion.
    Wei Zheng, Shuo Chen*, Zhenyong Fu, Jun Li, Jian Yang.
    Information Sciences (INS), 2023.

  6. Learnable Low-Rank Latent Dictionary for Subspace Clustering.
    Yesong Xu, Shuo Chen, Jun Li, Lei Luo, Jian Yang.
    Pattern Recognition (PR), 2021.

  7. Feature Selection Boosted by Unselected Features.
    Wei Zheng, Shuo Chen, Zhenyong Fu, Hui Yan, Fa Zhu, Jian Yang.
    IEEE Transactions on Neural Network and Learning System (T-NNLS), 2021.

  8. Autoencoder-Based Latent Block-Diagonal Representation for Subspace Clustering.
    Yesong Xu, Shuo Chen, Jun Li, Zongyan Han, Jian Yang.
    IEEE Transactions on Cybernetics (T-CYB), 2021.

  9. Generalization Bound Regularizer: A Unified Perspective for Understanding Weight Decay.
    Xiang Li, Shuo Chen, Jian Yang.
    Chinese Journal of Computers, 2021 (CCF A).

  10. Delta-norm based Robust Regression with Applications to Image Analysis.
    Shuo Chen, Jian Yang, Yang Wei, Lei Luo, Gui-Fu Lu, Chen Gong.
    IEEE Transactions on Cybernetics (T-CYB), 2019.

  11. Low-Rank Latent Pattern Approximation with Applications to Robust Image Classification.
    Shuo Chen, Jian Yang, Lei Luo, Yang Wei, Kai-Hua Zhang, Ying Tai.
    IEEE Transactions on Image Processing (T-IP), 2017.

Professional Activities

Area Chair

  • Neural Information Processing Systems (NeurIPS), 2022--2024

  • International Conference on Machine Learning (ICML), 2023--2024

  • International Conference on Learning Representations (ICLR), 2024

  • European Conference on Computer Vision (ECCV), 2024

Conference Reviewer

  • AAAI Conference on Artificial Intelligence (AAAI)

  • International Joint Conferences on Artificial Intelligence (IJCAI)

  • International Conference on Machine Learning (ICML)

  • Neural Information Processing Systems (NeurIPS)

  • International Conference on Learning Representations (ICLR)

  • IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR)

  • International Conference on Computer Vision (ICCV)

Journal Reviewer

  • Journal of Machine Learning Research (JMLR)

  • IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI)

  • IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS)

  • IEEE Transactions on Image Processing (IEEE TIP)

  • IEEE Transactions on Cybernetics (IEEE TCYB)

  • Machine Learning Journal (MLJ)

  • International Journal on Computer Vision (IJCV)

Workshop Organizer / Program Chair

  • International Workshop on Weakly Supervised Learning, 2023